Optimization design simulation analysis method for electromechanical actuator

Abstract

The invention discloses an electromechanical actuator optimization design simulation analysis method. The method is specifically implemented according to the following steps: step 1, establishing an electromechanical actuator model based on an AMESim environment; 2, determining a parameter range of each component in the electromechanical actuator model in the step 1, and obtaining a parameter influence rule; and step 3, adding an optimization design auxiliary module in the electromechanical actuator model in the step 1, establishing an electromechanical actuator optimization design model, dynamically adjusting the parameter range in the step 2 as the input of the electromechanical actuator optimization design model, and obtaining optimization design parameters. The method solves the problem that during simulation analysis of the electromechanical actuator in the prior art, control-mechanical full-system optimization design is not carried out on the electromechanical actuator, and the accuracy of dynamic performance output of the system is affected.

Description

Technical Field

[0001] The invention belongs to the technical field of aircraft power electric actuation systems and relates to an optimization design simulation analysis method for an electromechanical actuator. Background Art

[0002] As future aircraft and weapons are moving towards full electrification, the power-by-wire actuation system is gradually becoming a new type of control surface actuator for the flight control system. There are two main forms of power-by-wire: Electro-Hydrostatic Actuator (EHA) and Electro-Mechanical Actuator (EMA). Among them, the electromechanical actuator is the actuator of the aircraft power-by-wire control system, an important component of the flight control system, and one of the key technologies in more-electric / all-electric aircraft. The electromechanical actuator is mainly composed of three parts: the motor and its controller, the reduction mechanism, and the actuator (ball screw or planetary roller screw). It is a multi-variable, strongly coupled mechatronic complex system composed of two subsystems: control and mechanics.

[0003] Chinese patent "A roller screw electromechanical actuator" (application date: 2016.06.29; application number: CN201610497636.0; announcement date: 2016.10.05; publication number: CN105990951A) discloses a roller screw electromechanical actuator, which mainly includes a permanent magnet synchronous servo motor, a reducer, a planetary roller screw pair, a screw support bearing, a locking nut, an actuator rod, a first and a second actuator housing, and upper and lower ears; the permanent magnet synchronous servo motor is connected to the reducer input end through a flat key, the reducer output end is connected to the planetary roller screw through a spline connection, the screw nut is connected and fixed to the actuator rod through a screw, the roller screw pair is radially fixed through the screw support bearing and the actuator housing, and finally the bearing is locked by the locking nut. When the servo motor drives the reducer to drive the screw to rotate, the actuator rod can only perform reciprocating linear motion along the axial direction; it solves the problems of short zero position size, long positive and negative strokes, large load force, and high structural strength of high-power electromechanical actuators. The invention optimizes the design of the internal structure bearing structure, but does not involve the optimization design of control parameters. There is a certain fluctuation in the parameters, which cannot meet the dynamic performance indicators and affect the stability of the system during operation.

[0004] The electromechanical actuator is a typical complex electromechanical system. The system performance depends not only on the mechanical system design, but also on the control system performance. The motion characteristics and dynamic characteristics of the electromechanical actuator are not only related to the structural parameters of the machine itself, but also to the control parameters, characteristic parameters and dynamic performance. At present, the research on electromechanical actuators mainly focuses on structural design, control method design, health status assessment, etc. There are few studies on the control-mechanical system optimization design of electromechanical actuators. If the motion parameters are directly used as the input of the drive control system and the current of the control loop is converted into force and fed back to the simulation system, the required data volume is large, the calculation time is long, and the accuracy of the analysis cannot be guaranteed, which has a certain impact on the accuracy of the system dynamic performance analysis. Summary of the invention

[0005] The purpose of the present invention is to provide an optimization design simulation analysis method for an electromechanical actuator, which solves the problem that in the prior art electromechanical actuator simulation analysis, the electromechanical actuator is not controlled-mechanically optimized throughout the entire system, which affects the accuracy of the system's dynamic performance output.

[0006] The technical solution adopted by the present invention is a method for optimizing the design and simulation analysis of an electromechanical actuator, which is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0007] The present invention is also characterized in that: The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor adopts a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

[0008] In step 1, the gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw, which acts as an actuator to drive the load to move; the rotor magnetic pole position sensor converts the displacement output by the output rod into a signal, and the error between the position sensor output signal and the input command is used as the input of the PID controller, and the output of the PID controller is used as the control signal of the gear reducer.

[0009] In step 1, the gear reducer adopts the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears; the influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, tooth clearance, gear moment of inertia, and viscous friction coefficient considering gear meshing; the mechanical parameters include module, center distance, helix angle, tooth width, and pressure angle; the material parameters include Young's modulus and Poisson's ratio.

[0010] In step 1, the planetary roller screw adopts the SRWNT1 model to define the nominal diameter, lead and parameters of the screw, including the contact stiffness, contact damping and Coulomb friction coefficient between the screw and the nut.

[0011] Step 2 is as follows: the input command is a step signal, and the batch processing function of AMESim is used to determine the three control parameter ranges of the motor proportional link P, integral link I, and differential link D; the two mechanical parameter ranges of the gear reducer stiffness and clearance; the two mechanical parameter ranges of the planetary roller screw clearance and stiffness, and observe the influence of parameter changes on the step response.

[0012] The specific process of step 3 is as follows: Step 3.1, add the optimization design auxiliary module, through the product of the absolute value of the error and the time interval, after the integration link, it becomes the cumulative integral error, and the optimization is completed when the cumulative integral error is defined as the minimum. k / s back, k / s In k It is only to adjust the numerical precision and obtain the EndITAE at the end time; Step 3.2: Set the parameter variables to be optimized, and set the upper and lower limits of the optimization parameters according to the parameter range in step 2. Obtain the optimized design parameters through the electromechanical actuator optimization design model.

[0013] The specific process of step 3 is as follows: The expression for adding the optimization design auxiliary module is: (1) In the formula, x is the time interval, y is the error, abs( y ) is the absolute value of the error. The specific process of step 3.2 is as follows: Step 3.2.1. Select the optimization object in the Simple output parameters tab, drag the output of the integral module into the window, which is the final ITAE result, and define the variable as ITAE. Step 3.2.2, in the label of Compound output parameters, add the variable "globMax(ITAE)", globMax is the global maximum result, if the maximum integral sum is minimum, the optimization goal can be achieved; Step 3.2.3. Select "Mode--analysis--design exploration" mode--analysis--design exploration tab, select the parameters to be optimized, check EndITAE as Outputs output, and after the run is completed, you can see the optimized parameters and EndITAE values ​​in the run information prompt bar.

[0014] The beneficial effects of the present invention are as follows: the electromechanical actuator optimization design simulation analysis method of the present invention establishes an electromechanical actuator optimization design model, analyzes the parameter variation range of each component, determines the control-mechanical whole system optimization design parameters, accurately simulates the motion control performance of the electromechanical actuator, improves the reliability of simulation analysis, effectively improves the overall design efficiency, saves design costs, helps to improve corporate benefits, and is of great significance for guiding the structural design of electromechanical actuators and improving the dynamic output of aircraft actuation systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the electromechanical actuator optimization design model established in the AMESim environment of the present invention; Figure 2 It is a schematic diagram of the influence of the step response of the P proportional parameter; Figure 3 It is a schematic diagram of the influence of the step response of the I integral parameter; Figure 4 It is a schematic diagram of the influence of the step response of the D differential parameter; Figure 5 It is a schematic diagram of the influence of the step response of the clearance parameters of the gear reducer; Figure 6 It is a schematic diagram of the influence of step response of gear reducer stiffness parameters; Figure 7 It is a schematic diagram of the influence of the step response of the clearance parameters of the planetary roller screw; Figure 8 It is a schematic diagram of the influence of step response of the stiffness parameters of planetary roller screws; Fig. 9 This is a schematic diagram of the comparison results of the step response before and after the optimization of the motor PID control parameters; Fig.10 It is a schematic diagram of the comparison results of step response before and after the gear reducer parameter optimization; Fig.11This is a schematic diagram of the step response comparison results before and after the planetary roller screw parameter optimization; Fig.12 It is a schematic diagram of the step response comparison results before and after the overall parameter optimization. DETAILED DESCRIPTION

[0016] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] Example 1 The electromechanical actuator optimization design simulation analysis method of the present invention is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0018] Example 2 The electromechanical actuator optimization design simulation analysis method of the present invention is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor adopts a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

[0019] The gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw. The planetary roller screw acts as an actuator to drive the load to move. The rotor magnetic pole position sensor converts the displacement output by the output rod into a signal. The error between the position sensor output signal and the input command is used as the input of the PID controller. The output of the PID controller is used as the control signal of the gear reducer.

[0020] The gear reducer uses the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears.

[0021] The influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, backlash, gear moment of inertia, and viscous friction coefficient of gear meshing.

[0022] Mechanical parameters include modulus, center distance, helix angle, tooth width, and pressure angle; material parameters include Young's modulus and Poisson's ratio.

[0023] The planetary roller screw adopts the SRWNT1 model to define the nominal diameter and lead of the screw as well as the parameters, including the contact stiffness, contact damping and Coulomb friction coefficient between the screw and the nut.

[0024] Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0025] Example 3 The electromechanical actuator optimization design simulation analysis method of the present invention is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor adopts a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

[0026] The gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw. The planetary roller screw acts as an actuator to drive the load to move. The rotor magnetic pole position sensor converts the displacement output by the output rod into a signal. The error between the position sensor output signal and the input command is used as the input of the PID controller. The output of the PID controller is used as the control signal of the gear reducer.

[0027] The gear reducer uses the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears.

[0028] The influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, backlash, gear moment of inertia, and viscous friction coefficient of gear meshing.

[0029] Mechanical parameters include modulus, center distance, helix angle, tooth width, and pressure angle; material parameters include Young's modulus and Poisson's ratio.

[0030] The planetary roller screw adopts the SRWNT1 model to define the nominal diameter and lead of the screw as well as the parameters, including the contact stiffness, contact damping and Coulomb friction coefficient between the screw and the nut.

[0031] Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 2 is as follows: the input command is a step signal, and the batch processing function of AMESim is used to determine the three control parameter ranges of the motor proportional link P, integral link I, and differential link D; the two mechanical parameter ranges of the gear reducer stiffness and clearance; the two mechanical parameter ranges of the planetary roller screw clearance and stiffness, and observe the influence of parameter changes on the step response.

[0032] P ratio link: 1) Influence on dynamic characteristics: proportionality coefficient K P Increase, so that the electromechanical actuator moves more sensitively and faster. K P Too large, the oscillation frequency will increase and the adjustment time will be longer; K P If the value is too large, the electromechanical actuator will become unstable. K P If it is too small, the electromechanical actuator will move slowly; 2) Impact on steady-state characteristics: Increase the proportionality factor K P , when the electromechanical actuator is stable, the steady-state error can be reduced e ss , improve control accuracy, but increase K P Just reduce e ss , but it cannot completely eliminate the steady-state error.

[0033] In PID-controlled electromechanical actuators, the responses to changes in set values ​​and external disturbances are different, and the performance requirements for the two are also different in engineering applications. Changes in set values ​​generally require certain prerequisites to be met, such as fast tracking without overshoot; for external disturbances, it is hoped that the electromechanical actuator will quickly overcome them with a certain attenuation ratio.

[0034] I Points Section: The introduction of integral action is mainly to ensure that the controlled quantity tracks the set value without static error in steady state. Its influence on the performance of electromechanical actuator is reflected in the following two aspects: 1) Influence on dynamic characteristics: Integral action usually reduces the stability of electromechanical actuator. 2) Influence on steady-state characteristics: Integral action can eliminate the steady-state error of electromechanical actuator and improve the control accuracy of electromechanical actuator.

[0035] D Differentiation link: The differential action is usually combined with the proportional action or the integral action to form PD control or PID control. The introduction of the differential action is mainly to improve the stability and dynamic characteristics of the electromechanical actuator. If the overshoot is small and the adjustment time is shortened, the proportional control can be increased, the steady-state error can be reduced, and the control accuracy can be improved. T D When it is too large, the overshoot is large and the adjustment time is long; T D When it is too small, the overshoot is larger and the adjustment time is longer; only when it is appropriate can a satisfactory transition process be obtained.

[0036] Through batch processing of the gear reducer clearance factors, the backlash parameters in the gear model are changed and the clearance changes are set. Since the gear reducer is in the middle link of the electromechanical actuator, the change in the gear reducer clearance value is small relative to the electromechanical actuator as a whole, and the effect on the response speed and steady-state error is negligible. Therefore, the range of the gear reducer clearance is set to 0-0.1 mm.

[0037] Through batch processing of the gear reducer stiffness factors, the contact stiffness parameters in the gear reducer model are changed and the stiffness change is set. Since the gear reducer is in the middle link of the electromechanical actuator, the change of the gear reducer stiffness is small relative to the electromechanical actuator as a whole. The overall stiffness of the electromechanical actuator is equivalent to the stiffness of each link connected in series, that is, The overall stiffness is determined by the smallest stiffness among them, and the change of the gear reducer stiffness has little effect on the overall stiffness, and the effect on the response speed and steady-state error is negligible.

[0038] Through batch processing of planetary roller screw clearance factors, the planetary roller screw clearance change is set. In electromechanical actuators, the clearance affects not only the control accuracy, but also has a significant impact on stability. The larger the clearance, the larger the fluctuation amplitude of the electromechanical actuator response and the higher the frequency. The planetary roller screw clearance is an important nonlinear factor affecting the tracking accuracy of the electromechanical actuator. The influence of the clearance can be compensated by improving the processing and assembly accuracy of the transmission parts, reducing the clearance or using various mechanical or control methods. Through batch processing of planetary roller screw stiffness factors, the planetary roller screw stiffness change is set. The smaller the planetary roller screw stiffness value, the worse the stability of the electromechanical actuator, the longer the response time, and the slower the response speed; when the electromechanical actuator inputs load force, the larger the stiffness value, the smaller the fluctuation amplitude, the easier it is to reach a steady state, and the smaller the steady-state error.

[0039] Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0040] Example 4 The electromechanical actuator optimization design simulation analysis method of the present invention is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor adopts a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

[0041] The gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw. The planetary roller screw acts as an actuator to drive the load to move. The rotor magnetic pole position sensor converts the displacement output by the output rod into a signal. The error between the position sensor output signal and the input command is used as the input of the PID controller. The output of the PID controller is used as the control signal of the gear reducer.

[0042] The gear reducer uses the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears.

[0043] The influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, backlash, gear moment of inertia, and viscous friction coefficient of gear meshing.

[0044] Mechanical parameters include modulus, center distance, helix angle, tooth width, and pressure angle; material parameters include Young's modulus and Poisson's ratio.

[0045] The planetary roller screw adopts the SRWNT1 model to define the nominal diameter and lead of the screw as well as the parameters, including the contact stiffness, contact damping and Coulomb friction coefficient between the screw and the nut.

[0046] Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 2 is as follows: the input command is a step signal, and the batch processing function of AMESim is used to determine the three control parameter ranges of the motor proportional link P, integral link I, and differential link D; the two mechanical parameter ranges of the gear reducer stiffness and clearance; the two mechanical parameter ranges of the planetary roller screw clearance and stiffness, and observe the influence of parameter changes on the step response.

[0047] P ratio link: 1) Influence on dynamic characteristics: proportionality coefficient K P Increase, so that the electromechanical actuator moves more sensitively and faster. K P Too large, the oscillation frequency will increase and the adjustment time will be longer; KP If the value is too large, the electromechanical actuator will become unstable. K P If it is too small, the electromechanical actuator will move slowly; 2) Impact on steady-state characteristics: Increase the proportionality coefficient K P , when the electromechanical actuator is stable, the steady-state error can be reduced e ss , improve control accuracy, but increase K P Just reduce e ss , but it cannot completely eliminate the steady-state error.

[0048] In PID-controlled electromechanical actuators, the responses to changes in set values ​​and external disturbances are different, and the performance requirements for the two are also different in engineering applications. Changes in set values ​​generally require certain prerequisites to be met, such as fast tracking without overshoot; for external disturbances, it is hoped that the electromechanical actuator will quickly overcome them with a certain attenuation ratio.

[0049] I Points Section: The introduction of integral action is mainly to ensure that the controlled quantity tracks the set value without static error in steady state. Its influence on the performance of electromechanical actuator is reflected in the following two aspects: 1) Influence on dynamic characteristics: Integral action usually reduces the stability of electromechanical actuator. 2) Influence on steady-state characteristics: Integral action can eliminate the steady-state error of electromechanical actuator and improve the control accuracy of electromechanical actuator.

[0050] D Differentiation link: The differential action is usually combined with the proportional action or the integral action to form PD control or PID control. The introduction of the differential action is mainly to improve the stability and dynamic characteristics of the electromechanical actuator. If the overshoot is small and the adjustment time is shortened, the proportional control can be increased, the steady-state error can be reduced, and the control accuracy can be improved. T D When it is too large, the overshoot is large and the adjustment time is long; T D When it is too small, the overshoot is larger and the adjustment time is longer; only when it is appropriate can a satisfactory transition process be obtained.

[0051] Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0052] An optimization design auxiliary module is added. The product of the absolute value of the error and the time interval is converted into a cumulative integral error after an integration step. The optimization is completed when the cumulative integral error is defined as the minimum.

[0053] The expression for adding the optimization design auxiliary module is: (1) In the formula, x is the time interval, y is the error, abs( y ) is the absolute value of the error.

[0054] Example 5 The electromechanical actuator optimization design simulation analysis method of the present invention is specifically implemented according to the following steps: Step 1: Establish an electromechanical actuator model based on AMESim environment; The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor adopts a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

[0055] The gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw. The planetary roller screw acts as an actuator to drive the load to move. The rotor magnetic pole position sensor converts the displacement output by the output rod into a signal. The error between the position sensor output signal and the input command is used as the input of the PID controller. The output of the PID controller is used as the control signal of the gear reducer.

[0056] The gear reducer uses the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears.

[0057] The influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, backlash, gear moment of inertia, and viscous friction coefficient of gear meshing.

[0058] Mechanical parameters include modulus, center distance, helix angle, tooth width, and pressure angle; material parameters include Young's modulus and Poisson's ratio.

[0059] The planetary roller screw adopts the SRWNT1 model to define the nominal diameter and lead of the screw as well as the parameters, including the contact stiffness, contact damping and Coulomb friction coefficient between the screw and the nut.

[0060] Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 2 is as follows: the input command is a step signal, and the batch processing function of AMESim is used to determine the three control parameter ranges of the motor proportional link P, integral link I, and differential link D; the two mechanical parameter ranges of the gear reducer stiffness and clearance; the two mechanical parameter ranges of the planetary roller screw clearance and stiffness, and observe the influence of parameter changes on the step response.

[0061] P ratio link: 1) Influence on dynamic characteristics: proportionality coefficient K P Increase, so that the electromechanical actuator moves more sensitively and faster. K P Too large, the oscillation frequency will increase and the adjustment time will be longer; K P If the value is too large, the electromechanical actuator will become unstable. K P If it is too small, the electromechanical actuator will move slowly; 2) Impact on steady-state characteristics: Increase the proportionality coefficient K P , when the electromechanical actuator is stable, the steady-state error can be reduced e ss , improve control accuracy, but increase K P Just reduce e ss , but it cannot completely eliminate the steady-state error.

[0062] In PID-controlled electromechanical actuators, the responses to changes in set values ​​and external disturbances are different, and the performance requirements for the two are also different in engineering applications. Changes in set values ​​generally require certain prerequisites to be met, such as fast tracking without overshoot; for external disturbances, it is hoped that the electromechanical actuator will quickly overcome them with a certain attenuation ratio.

[0063] I Points Section: The introduction of integral action is mainly to ensure that the controlled quantity tracks the set value without static error in steady state. Its influence on the performance of electromechanical actuator is reflected in the following two aspects: 1) Influence on dynamic characteristics: Integral action usually reduces the stability of electromechanical actuator. 2) Influence on steady-state characteristics: Integral action can eliminate the steady-state error of electromechanical actuator and improve the control accuracy of electromechanical actuator.

[0064] D Differentiation link: The differential action is usually combined with the proportional action or the integral action to form PD control or PID control. The introduction of the differential action is mainly to improve the stability and dynamic characteristics of the electromechanical actuator. If the overshoot is small and the adjustment time is shortened, the proportional control can be increased, the steady-state error can be reduced, and the control accuracy can be improved. T D When it is too large, the overshoot is large and the adjustment time is long; T D When it is too small, the overshoot is larger and the adjustment time is longer; only when it is appropriate can a satisfactory transition process be obtained.

[0065] Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1 to establish an optimization design model for the electromechanical actuator, such as Figure 1 As shown, the black dashed box dynamically adjusts the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimized design parameters.

[0066] The specific process of step 3 is as follows: Step 3.1, add the optimization design auxiliary module, through the product of the absolute value of the error and the time interval, after the integration link, it becomes the cumulative integral error, and the optimization is completed when the cumulative integral error is defined as the minimum. k / s back, k / s In k It is only to adjust the numerical precision and obtain the EndITAE at the end time; The expression for adding the optimization design auxiliary module is: (1) In the formula, x is the time interval, y is the error, abs( y ) is the absolute value of the error. Step 3.2: Set the parameter variables to be optimized, and set the upper and lower limits of the optimization parameters according to the parameter range in step 2. Obtain the optimized design parameters through the electromechanical actuator optimization design model.

[0067] Step 3.2.1. Select the optimization object in the Simple output parameters tab, drag the output of the integral module into the window, which is the final ITAE result, and define the variable as ITAE. Step 3.2.2, in the label of Compound output parameters, add the variable "globMax(ITAE)", globMax is the global maximum result, if the maximum integral sum is minimum, the optimization goal can be achieved; Step 3.2.3. Select "Mode--analysis--design exploration" mode--analysis--design exploration tab, select the parameters to be optimized, check EndITAE as Outputs output, and after the run is completed, you can see the optimized parameters and EndITAE values ​​in the run information prompt bar.

[0068] Example 6 On the basis of Example 5, in step 1 of this example, the electromechanical actuator in the electromechanical actuator model established based on the AMESim environment has a rated output force of not less than 21000 N, a maximum output force of not less than 51660 N, a rated speed of not less than 104 mm / s, a planetary roller screw pitch of 2 mm, 5 screw heads, and a lead of 10 mm.

[0069] According to the design requirements, the screw speed is (104 mm / s) / (10 mm / r)=10.4 rps=624 rpm.

[0070] A planetary gear reducer is used for deceleration with a reduction ratio of 4, so the rated output speed of the motor is 2496 rpm, that is, a motor with a rated speed of 3000 rpm is selected. The maximum speed of the gear in the rack and pinion is 750 rpm. The rack is required to move 10 mm for every rotation of the gear, and the radius of the gear is calculated to be 10 mm / 2pi.

[0071] Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; like Figure 2 As shown in the figure, when the P proportional link coefficient increases to 700, overshoot begins to appear, and the proportional link coefficient and the static error do not show a linear change law. K P =400 has the smallest static error, so the range of setting the P proportional link coefficient is 100~700.

[0072] like Figure 3 As shown in the figure, when the I integral link coefficient increases to 10, overshoot begins to appear. K I =50 has the smallest static error. K I =60, and then it changes according to the rule that the smaller the integral coefficient is, the larger the error is. When the integral coefficient is 0.01 and 0.1, the integral error is almost the same, so the range of the I integral link coefficient is set to 0.1~10.

[0073] like Figure 4As shown in the figure, when the D differential link coefficient increases, the rise time becomes longer, and when the coefficient increases to 10, the response changes suddenly. As the D differential link coefficient increases from 0.01 to 40, the static error gradually increases, so the range of setting the D differential link coefficient is 0.01 to 10.

[0074] Gear reducer clearance like Figure 5 As shown in the figure, it is the batch processing result diagram of the clearance factor of the gear reducer. The clearance parameters in the gear model are changed, and the clearance is set from 0 to 0.1 mm. After multiple amplifications, the results show that the change of the clearance value of the gear reducer has little effect on the response speed and steady-state error. This is because the reduction mechanism is in the middle link of the electromechanical actuator, so the change of its clearance is small relative to the overall electromechanical actuator, and its effect can be ignored. Therefore, the range of the gear reducer clearance is set to 0 to 0.1 mm.

[0075] Gear reducer stiffness like Figure 6 As shown in the figure, it is the batch processing result diagram of the gear reducer stiffness factor. The contact stiffness parameter in the gear reducer model is changed and the stiffness is set from 1×10 7 N / m~1×10 9 After multiple amplifications, the results show that the change in the stiffness value of the gear reducer has little effect on the response speed and steady-state error. This is because the reduction mechanism is in the middle link of the electromechanical actuator, so the change in its stiffness is small relative to the electromechanical actuator as a whole, and its effect can be ignored. The overall stiffness of the electromechanical actuator is equivalent to the stiffness of each link connected in series, that is, The overall stiffness is determined by the smallest stiffness, and the change of the gear reducer stiffness has little effect on the overall stiffness. After considering the processing level, the range of setting the gear reducer stiffness is 1×10 8 N / m~1×10 9 N / m.

[0076] Planetary roller screw clearance like Figure 7As shown in the figure, it is a batch processing result diagram of the planetary roller screw clearance factor. The clearance is an important nonlinear factor affecting the tracking accuracy of the system. It can usually be compensated by improving the processing and assembly accuracy of the transmission parts, reducing the clearance, or using various mechanical or control methods. The planetary roller screw clearance is set to change from 0 to 0.1 mm. The results show that in the electromechanical actuator, the clearance affects not only the control accuracy, but also has a significant impact on the stability. The larger the clearance, the larger the fluctuation amplitude of the electromechanical actuator response and the higher the frequency. When the clearance increases to 0.07 mm, the fluctuation amplitude is very large and overshoot occurs; the smaller the clearance, the smaller the steady-state error. When the clearance value decreases from 0.01 mm, the steady-state error does not change much. Therefore, the range of the actuator clearance is set to 0.01 to 0.1 mm.

[0077] Planetary roller screw stiffness like Figure 8 The figure shows the batch processing result of the planetary roller screw stiffness factor. In structural finite element analysis, 1%-5% is often used. Here we take 1%. The damping ratio (i.e. f )for . Set the planetary roller screw stiffness from 5×10 7 N / m~5×10 9 N / m changes. The smaller the stiffness value of the planetary roller screw, the worse the stability of the electromechanical actuator, the longer the response time, and the slower the response speed. When the stiffness increases to 1×10 8 N / m, the fluctuation of the initial response of the electromechanical actuator is very small. When it increases to 1×10 8 N / m, the response speed is almost the same; when the load force is input, the larger the stiffness value, the smaller the fluctuation amplitude, the easier it is to reach a steady state, and the smaller the steady-state error. When the stiffness reaches 1×10 9 N / m, when the load force is input, the fluctuation is small and the steady state is reached quickly. Therefore, after considering the processing level, the range of setting the actuator stiffness is 1×10 8 N / m~1×10 9 N / m.

[0078] Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

[0079] The purpose of establishing an optimization design model is to minimize the integral of the absolute value of the error in the dynamic adjustment process, and to perform optimization design based on the parameter ranges of the above-mentioned components and their influence rules. Figure 1The optimized design model is in the black dotted box. The clock generates a time segment, and the output result is the product of the absolute value of the error and the time interval. After the integration link, it becomes the accumulated integral error.

[0080] Then click Export setup in the Setting menu, set the parameters to be optimized in the Export parameters dialog box that pops up (drag the module parameters to be optimized in), and set the upper and lower limits of the optimization parameters according to the above parameter range. Then select the optimization object in Simple output parameters and export the integral module. k / s Drag the output of into the window, which is the final ITAE result, and define the variable as ITAE.

[0081] Finally, in Compound output parameters, click “Add” to add a variable with the expression globMax(ITAE) (globMax means the global maximum result). If the maximum integral and the minimum (the default is the minimum when AMESim optimizes the design), the optimization goal can be achieved.

[0082] Then click "Mode--analysis--design exploration", right-click in the Optimization tab, select "New Study", select the parameters to be optimized in the pop-up dialog box, and check EndITAE as Outputs. After the run is completed, you can see the optimized parameters and EndITAE values ​​in the run information prompt bar.

[0083] Motor PID control parameter optimization The optimized parameters include: motor PID control parameters (proportional link coefficient, integral link coefficient, differential link coefficient), and the remaining parameters remain unchanged before and after optimization, including: gear reducer parameters (stiffness, clearance), planetary roller screw parameters (stiffness, clearance). The optimization results are as follows Fig. 9 As shown in the figure, the results show that the response speed of the electromechanical actuator is significantly faster, the steady-state error is reduced, but the stability is reduced, which is due to the increase in gain. The optimized PID control parameters are: K P =385.5, K I =0.134, K D =0.481.

[0084] Gear reducer parameter optimization The optimized parameters include: gear reducer parameters (stiffness, clearance), and the remaining parameters remain unchanged before and after optimization, including: motor PID control parameters (proportional link coefficient, integral link coefficient, differential link coefficient), planetary roller screw parameters (stiffness, clearance). The optimization results are as follows Fig.10 The results show that after optimization, the electromechanical actuator has a fast response speed and a small steady-state error, achieving the purpose of optimization. The optimized gear reducer parameters are: stiffness = 5×10 8 N / m, gap = 5.038 × 10 -2 mm, which is basically the same as the parameters before optimization, indicating that the change of gear reducer parameters has little effect on the optimization results, which is consistent with the previous analysis that the reduction mechanism has little effect on the output of the electromechanical actuator.

[0085] Planetary Roller Screw Parameter Optimization The optimized parameters include: planetary roller screw parameters (stiffness, clearance), and the remaining parameters remain unchanged before and after optimization, including: motor PID control parameters (proportional link coefficient, integral link coefficient, differential link coefficient), gear reducer parameters (stiffness, clearance). The optimization results are as follows Fig.11 As shown in the figure, the results show that the response fluctuation is reduced, the stability is improved, and the steady-state error is reduced. This is because the stiffness value of the planetary roller screw increases after optimization, and the clearance value has reached the minimum value within the given range. The optimization results are consistent with the influence of the planetary roller screw parameters on the system. The parameters of the actuator after optimization are: stiffness = 1×10 9 N / m, gap = 0.01 mm, the optimized values ​​of stiffness and gap both reach the optimal values ​​within the given parameter range. This is because the greater the stiffness and the smaller the gap, the better the system rapidity and the smaller the steady-state error.

[0086] Overall parameter optimization The optimization parameters include: motor PID control parameters (proportional link coefficient, integral link coefficient, differential link coefficient), gear reducer parameters (stiffness, clearance), planetary roller screw parameters (stiffness, clearance). The optimization results are as follows: Fig.12 As shown, the results show that the response speed is significantly accelerated, the stability is improved, and the steady-state error is reduced. The optimized parameters are: PID control parameters K P =277.558, K I =0.095, K D =0.863; Gear reducer parameters: stiffness = 4.9×10 8 N / m, clearance = 0.006 mm; planetary roller screw parameters: stiffness = 9.9×10 8 N / m, gap = 0.009 mm.

[0087] In summary, in order to ensure that the electromechanical actuator has good dynamic response characteristics and small steady-state errors, from the control aspect, the controller parameters, such as PID parameters, are adjusted through software and certain control strategies to improve the dynamic response characteristics of the electromechanical actuator. From the mechanical aspect, the materials of the transmission mechanism are reasonably used to improve the rigidity of the components; anti-backlash measures are adopted: anti-backlash gear structure is adopted, double nut pre-tightening method is adopted to eliminate the axial clearance between the roller and nut in the planetary roller screw, or anti-wear materials are adopted; and lubrication conditions are improved to reduce the friction torque of the system.

[0088] The electromechanical actuator optimization design simulation analysis method of the present invention establishes an electromechanical actuator optimization design model, analyzes the parameter variation range of each component, determines the control-mechanical whole system optimization design parameters, reduces the complexity of modeling, greatly improves the efficiency and accuracy of current electromechanical actuator simulation analysis, and can provide a basis for analyzing the influence of electromechanical actuator stability. It is of great significance to guiding the structural design of electromechanical actuators and improving the dynamic output of aircraft actuation systems.

Claims

1. The electromechanical actuator optimization design simulation analysis method is characterized by: Follow the steps below to implement it: Step 1: Establish an electromechanical actuator model based on AMESim environment; Step 2, determine the parameter range of each component in the electromechanical actuator model in step 1, and obtain the parameter influence law; Step 3: Add an optimization design auxiliary module to the electromechanical actuator model in step 1, establish an electromechanical actuator optimization design model, and use the dynamic adjustment of the parameter range in step 2 as the input of the electromechanical actuator optimization design model to obtain the optimization design parameters.

2. The electromechanical actuator optimization design simulation analysis method according to claim 1 is characterized in that: The electromechanical actuator model in step 1 includes a motor, a PID controller, a gear reducer and a planetary roller screw; the motor is a permanent magnet brushless DC motor, and the permanent magnet brushless DC motor includes a motor body and a rotor magnetic pole position sensor.

3. The electromechanical actuator optimization design simulation analysis method according to claim 2, characterized in that: In step 1, the gear reducer converts the input control signal into a mechanical signal and outputs it to the planetary roller screw, which acts as an actuator to drive the load to move; the rotor magnetic pole position sensor converts the displacement output by the output rod into a signal, and the error between the position sensor output signal and the input instruction is used as the input of the PID controller, and the output of the PID controller is used as the control signal of the gear reducer.

4. The electromechanical actuator optimization design simulation analysis method according to claim 3 is characterized in that: In the step 1, the gear reducer adopts the TRGT01B model in the AMESim mechanical library to define the influencing factors of the two meshing gears; the influencing factors include mechanical parameters, material parameters, and contact stiffness, contact damping, tooth clearance, gear moment of inertia, and viscous friction coefficient considering gear meshing; the mechanical parameters include module, center distance, helix angle, tooth width, and pressure angle; the material parameters include Young's modulus and Poisson's ratio.

5. The electromechanical actuator optimization design simulation analysis method according to claim 4 is characterized in that: In step 1, the planetary roller screw adopts the SRWNT1 model to define the nominal diameter and lead of the screw as well as parameters, wherein the parameters include the contact stiffness, contact damping, and Coulomb friction coefficient between the screw and the nut.

6. The electromechanical actuator optimization design simulation analysis method according to claim 5, characterized in that: The step 2 is specifically as follows: the input command is a step signal, and the batch processing function of AMESim is used to respectively determine the three control parameter ranges of the motor proportional link P, the integral link I, and the differential link D; the two mechanical parameter ranges of the gear reducer stiffness and clearance; the two mechanical parameter ranges of the planetary roller screw clearance and stiffness, and observe the influence of parameter changes on the step response.

7. The electromechanical actuator optimization design simulation analysis method according to claim 6, characterized in that: The specific process of step 3 is: Step 3.1, add optimization design auxiliary module, through the product of the absolute value of the error and the time interval, after the integration link, it becomes the cumulative integral error, define the cumulative integral error as the minimum, complete the optimization, after integration k / s back, k / s In k It is only to adjust the numerical precision and obtain the EndITAE at the end time; Step 3.2, set the parameter variables to be optimized, and set the upper and lower limits of the optimization parameters according to the parameter range in step 2, and obtain the optimized design parameters through the electromechanical actuator optimization design model.

8. The electromechanical actuator optimization design simulation analysis method according to claim 7, characterized in that: The specific process of step 3 is as follows: The expression for adding the optimization design auxiliary module is: （1） In the formula, x is the time interval, y is the error, abs( y ) is the absolute value of the error.

9. The electromechanical actuator optimization design simulation analysis method according to claim 8, characterized in that: The specific process of step 3.2 is as follows: Step 3.2.

1. Select the optimization object in the Simple output parameters tab, drag the output of the integral module into the window, which is the final ITAE result, and define the variable as ITAE. Step 3.2.2, in the label of Compound output parameters, add the variable "globMax(ITAE)", globMax is the global maximum result, if the maximum integral sum is minimum, the optimization goal can be achieved; Step 3.2.

3. Select "Mode--analysis--design exploration" mode--analysis--design exploration tab, select the parameters to be optimized, check EndITAE as Outputs output, and after the run is completed, you can see the optimized parameters and EndITAE values ​​in the run information prompt bar.

Images