Method for quickly selecting counter electromotive force compensation coefficient in motor control process

Abstract

The invention discloses a method for quickly selecting a counter electromotive force compensation coefficient in a motor control process, which comprises the following steps of: establishing a motor mathematical model: establishing typical voltage, flux linkage and torque mathematical models of a motor according to the type of the motor; and establishing a control strategy method model, wherein motor speed control generally comprises a current loop and a speed loop. The current loop is an inner loop, the control bandwidth of the current loop can be selected to be 1000-2000Hz in order not to influence the response rate of the outer loop, and the speed loop is an outer loop, and the control bandwidth is 1 / 3-1 / 5 of the inner loop; the influence of back electromotive force compensation on speed control is analyzed, the back electromotive force compensation is added into a typical motor control mathematical model, and a complete motor speed control mathematical model is established; and writing an optimal coefficient selection program by taking the back electromotive force compensation coefficient as a variable to obtain a value of an optimal back electromotive force compensation coefficient in a motor control process. According to the invention, high-precision control of the permanent magnet synchronous motor can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of motor control, and in particular to a method for quickly selecting a back electromotive force compensation coefficient during a motor control process. Background Art

[0002] With the development of power electronics technology and the upgrading of power electronics devices, the research and application of servo systems have made significant progress, changing the face of motion control. Motion control can generally be understood as the real-time control of the position and speed of mechanical moving parts so that they move according to the expected motion trajectory and specified motion parameters. A complete motion control system includes a motor, a driver, a feedback device, a motion controller, and a main controller. The motor, as a driving component, is an important link in the motion control system. When the motor is running, due to the interaction between the armature and the magnetic pole, an electromotive force is generated in the armature. This electromotive force is opposite to the electromotive force provided by the external power supply and increases with the increase of the motor speed. It is called back electromotive force. Since the back electromotive force is related to the motor speed, it will affect the speed control of the motor. Under normal circumstances, the back electromotive force compensation method can be used to reduce the impact of the back electromotive force on the motor control. The present invention will disclose a method for quickly selecting the back electromotive force compensation coefficient. Summary of the Invention

[0003] Purpose of the invention: To provide a method for quickly selecting a back electromotive force compensation coefficient during motor control, so as to solve the problem that the back electromotive force affects the speed control of the motor.

[0004] Technical solution:

[0005] A method for quickly selecting a back electromotive force compensation coefficient during a motor control process, the method comprising the following steps:

[0006] Step 1: Establish a typical motor control mathematical model based on the motor type;

[0007] Step 2: Select any control method to establish a control strategy method model to achieve control of the inner loop and outer loop of the motor, where the inner loop is the current loop and the outer loop is the speed loop;

[0008] Step 3: Add back-EMF compensation to the typical motor control mathematical model to establish a complete motor speed control mathematical model, analyze the impact of back-EMF compensation on the speed control of the motor in the motor speed control mathematical model, and identify the optimal back-EMF compensation coefficient through a cyclic simulation test in the motor speed control mathematical model.

[0009] In a further embodiment, in step 1, the selected parameters of the typical motor control mathematical model include voltage, flux linkage and torque.

[0010] In a further embodiment, in step 1, the expression of the typical motor control mathematical model established is:

[0011]

[0012] Where U is the power supply voltage (V), R is the motor resistance (Ω), L is the motor inductance (H), E is the motor back electromotive force (V), i is the motor control current (A), and k e is the motor back electromotive force coefficient (V·s / rad), ω is the motor speed (rad / s), T e is the electromagnetic torque of the motor (Nm), k t is the motor torque coefficient (Nm / A), T L is the motor load torque (Nm), J is the motor moment of inertia (kg·m 2 ), t is the time scale (s).

[0013] In a further embodiment, in step 2, an ADRC control strategy is selected to realize the control of the current loop and speed loop of the motor. The ADRC mainly consists of a tracking differentiator TD, an extended state observer ESO and a nonlinear state error feedback control law SEF.

[0014] In a further embodiment, the control steps of the ADRC control strategy are as follows:

[0015] Step 2-1: Current loop control strategy:

[0016] First, establish the extended state observer;

[0017] Performing Laplace transform on the voltage equation of formula (1) yields the current loop control object model:

[0018]

[0019] Convert equation (2) into state equation (3):

[0020]

[0021] in,

[0022] Treat x2=f(x1,ω(t),t) as a new unknown state variable and add it to the original system of formula (3). That is, a new state is expanded on the basis of the state of the original system of formula (3). The original system of formula (3) becomes a linear system:

[0023]

[0024] A nonlinear state observer ESO is established for this system:

[0025]

[0026] Among them, ε1 is the observation error value, z1 is the first state observed, z2 is the second state observed, β 01i =2ω oi ,ω oi =3ω ci ,ω ci The current loop bandwidth is 1500Hz.

[0027] Then calculate the feedback control law parameters, according to the empirical formula, k pi =ω ci ;

[0028] Step 2-2: Speed loop control strategy:

[0029] Similar to the current loop, analyze the values of the parameters in the speed loop ADRC. Speed loop bandwidth ω cv Take 500Hz, ω ov =3ω cv , β 01v =2ω ov 、 k pv =ω cv .

[0030] In a further embodiment, in step 3, based on the ADRC control strategy, the back electromotive force compensation coefficient n, the value range of n is 0 to 1, n is a variable, when n is closer to 1, the response speed of the motor is faster, and in this embodiment, when n is 0.9, the response speed of the motor is faster.

[0031] In a further embodiment, in step 2, a PID control strategy is selected to implement control of the current loop and speed loop of the motor.

[0032] In a further embodiment, the control steps using the PID control strategy are as follows:

[0033] Step 2-1: Current loop control strategy;

[0034] The current loop controller uses a parallel PI controller:

[0035]

[0036] Current loop controlled object model:

[0037]

[0038] The current loop system model is:

[0039]

[0040] make The current loop system model is simplified as:

[0041]

[0042] Where: k pi =ω i L, k ii =ω i R,ω i =1500rad / s,ω i is the current loop bandwidth;

[0043] Step 2-2: Speed loop control strategy;

[0044] The speed loop parameters are calculated in the same way as the current loop, k pv =2ω v J / k t , ω v =250rad / s,ω v is the speed loop bandwidth.

[0045] In a further embodiment, in the step 3, based on the PID control strategy, the back electromotive force compensation coefficient n, the value range of n is 0 to 1, when n is 0.3, the response speed of the motor is the fastest.

[0046] In a further embodiment, the step 3 of identifying the optimal back-electromotive force compensation coefficient through cyclic simulation specifically includes taking the back-electromotive force compensation coefficient as a variable, writing an optimal coefficient selection program, and obtaining the value of the optimal back-electromotive force compensation coefficient during the motor control process.

[0047] The beneficial effects of the present invention are as follows: in view of the influence of the back electromotive force generated by the interaction between the armature and the magnetic pole on the motor control when the motor is running, the present invention proposes a method for quickly selecting the back electromotive force compensation coefficient. The method offsets the influence of the back electromotive force on the motor speed control by adding a back electromotive force compensation term to the motor control model, thereby improving the motor control effect. The automatic cycle program is further used to quickly select the optimal value of the back electromotive force compensation coefficient to achieve the best compensation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a flow chart of a method for quickly selecting back-electromotive force compensation coefficient.

[0049] Figure 2 Schematic diagram of the ADRC control strategy in Example 1.

[0050] Figure 3 It is a control block diagram based on the ADRC control strategy in Example 1.

[0051] Figure 4 This is a complete motor speed control block diagram based on ADRC in Example 1.

[0052] Figure 5 It is a motor speed step response curve diagram based on ADRC in Example 1.

[0053] Figure 6 This is the control block diagram based on the PID control strategy in Example 2

[0054] Figure 7 This is the complete motor speed control block diagram based on PID in Example 2.

[0055] Figure 8 This is a graph of the motor speed step response based on PID in Example 2. DETAILED DESCRIPTION

[0056] In the following description, numerous specific details are provided to provide a more thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without one or more of these details. In other instances, certain technical features well known in the art are not described to avoid confusion with the present invention.

[0057] The present invention will be further described in detail below with reference to the accompanying drawings.

[0058] Example 1

[0059] Reference Figure 1-5 , is a method for quickly selecting a back electromotive force compensation coefficient in a motor control process disclosed in the present invention, the method comprising the following steps:

[0060] Step 1: Establish a typical motor control mathematical model based on the motor type

[0061] In step 1, the selected parameters of the typical motor control mathematical model include voltage, flux linkage and torque.

[0062] In step 1, the expression of the typical motor control mathematical model established is:

[0063]

[0064] Where U is the power supply voltage (V), R is the motor resistance (Ω), L is the motor inductance (H), E is the motor back electromotive force (V), i is the motor control current (A), and k eis the motor back electromotive force coefficient (V·s / rad), ω is the motor speed (rad / s), T e is the electromagnetic torque of the motor (Nm), k t is the motor torque coefficient (Nm / A), T L is the motor load torque (Nm), J is the motor moment of inertia (kg·m 2 ), t is the time scale (s).

[0065] Step 2: Select any control method to establish a control strategy method model to realize the control of the inner and outer loops of the motor. The inner loop is the current loop, and the outer loop is the speed loop. The motor speed control generally includes the current loop and the speed loop. The current loop is the inner loop. In order not to affect the response rate of the outer loop, the current loop control bandwidth can be selected as 1000~2000Hz. The speed loop is the outer loop, and the control bandwidth is 1 / 3~1 / 5 of the inner loop.

[0066] In step 2, the ADRC control strategy is selected to realize the control of the current loop and speed loop of the motor. ADRC mainly consists of a tracking differentiator TD, an extended state observer ESO, and a nonlinear state error feedback control law SEF. Its basic structure is as follows: Figure 2 As shown, this example is only for the first-order system.

[0067] The control steps of the ADRC control strategy are as follows:

[0068] Step 2-1: Current loop control strategy:

[0069] First, establish the extended state observer;

[0070] Performing Laplace transform on the voltage equation of formula (1) yields the current loop control object model:

[0071]

[0072] Convert equation (2) into state equation (3):

[0073]

[0074] in,

[0075] Treat x2=f(x1,ω(t),t) as a new unknown state variable and add it to the original system. That is, a new state is expanded based on the state of the original system, and the original system becomes a linear system:

[0076]

[0077] A nonlinear state observer ESO is established for this system:

[0078]

[0079] Among them, ε1 is the observation error value, z1 is the first state observed, z2 is the second state observed, β 01i =2ω oi ,ω oi =3ω ci ,ω ci The current loop bandwidth is 1500Hz.

[0080] Then calculate the feedback control law parameters, according to the empirical formula, k pi =ω ci ;

[0081] Step 2-2: Speed loop control strategy:

[0082] Similar to the current loop, analyze the values of the parameters in the speed loop ADRC. Speed loop bandwidth ω cv Take 500Hz, ω ov =3ω cv , β 01v =2ω ov 、 k pv =ω cv .

[0083] The control block diagram based on ADRC control strategy is as follows Figure 3 shown.

[0084] Step 3: Add back-EMF compensation to the typical motor control mathematical model to establish a complete motor speed control mathematical model, analyze the impact of back-EMF compensation on the speed control of the motor in the motor speed control mathematical model, and identify the optimal back-EMF compensation coefficient through a cyclic simulation test in the motor speed control mathematical model.

[0085] In step 3, based on the ADRC control strategy, the back electromotive force compensation coefficient n, the value range of n is 0~1, n is a variable. When n is closer to 1, the response speed of the motor is faster. n takes 0, 0.1, 0.2...1. When the back electromotive force compensation coefficient is different, the motor speed step response curve is as follows: Figure 5 As shown, it can be seen that when the back electromotive force compensation coefficient is closer to 1, the response of the motor is faster. Therefore, the back electromotive force compensation coefficient can be selected to be close to 1. Due to the influence of speed fluctuations or other interferences, it is not recommended to select the back electromotive force coefficient value as 1. Therefore, in this embodiment, n is taken as 0.9.

[0086] In step 3, the optimal back-electromotive force compensation coefficient is identified through cyclic simulation, specifically including taking the back-electromotive force compensation coefficient as a variable, writing an optimal coefficient selection program, and obtaining the value of the optimal back-electromotive force compensation coefficient in the motor control process.

[0087] Example 2

[0088] Reference Figure 1 、 6 , 7, 8, are a method for quickly selecting a back electromotive force compensation coefficient in a motor control process disclosed in the present invention, and the method includes the following steps:.

[0089] Step 1: Establish a typical motor control mathematical model based on the motor type

[0090] In step 1, the selected parameters of the typical motor control mathematical model include voltage, flux linkage and torque.

[0091] In step 1, the expression of the typical motor control mathematical model established is:

[0092]

[0093] Where U is the power supply voltage (V), R is the motor resistance (Ω), L is the motor inductance (H), E is the motor back electromotive force (V), i is the motor control current (A), and k e is the motor back electromotive force coefficient (V·s / rad), ω is the motor speed (rad / s), T e is the electromagnetic torque of the motor (Nm), k t is the motor torque coefficient (Nm / A), T L is the motor load torque (Nm), J is the motor moment of inertia (kg·m 2 ), t is the time scale (s).

[0094] Step 2: Select any control method to establish a control strategy method model to realize the control of the inner and outer loops of the motor. The inner loop is the current loop, and the outer loop is the speed loop. The motor speed control generally includes the current loop and the speed loop. The current loop is the inner loop. In order not to affect the response rate of the outer loop, the current loop control bandwidth can be selected as 1000~2000Hz. The speed loop is the outer loop, and the control bandwidth is one-third to one-fifth of the inner loop.

[0095] In step 2, a PID control strategy is selected to control the current loop and speed loop of the motor.

[0096] The control steps of the PID control strategy are as follows:

[0097] Step 2-1: Current loop control strategy;

[0098] The current loop controller uses a parallel PI controller:

[0099]

[0100] Current loop controlled object model:

[0101]

[0102] The current loop system model is:

[0103]

[0104] make The current loop system model is simplified as:

[0105]

[0106] Where: k pi =ω i L, k ii =ω i R,ω i =1500rad / s,ω i is the current loop bandwidth;

[0107] Step 2-2: Speed loop control strategy;

[0108] The speed loop parameters are calculated in the same way as the current loop, k pv =2ω v J / k t , ω v =250rad / s,ω v is the speed loop bandwidth.

[0109] The control block diagram based on PID control strategy is as follows Figure 6 shown.

[0110] Step 3: Add back-EMF compensation to the typical motor control mathematical model to establish a complete motor speed control mathematical model, analyze the impact of back-EMF compensation on the speed control of the motor in the motor speed control mathematical model, and identify the optimal back-EMF compensation coefficient through a cyclic simulation test in the motor speed control mathematical model.

[0111] In step 3, the optimal back-electromotive force compensation coefficient is identified through cyclic simulation, specifically including taking the back-electromotive force compensation coefficient as a variable, writing an optimal coefficient selection program, and obtaining the value of the optimal back-electromotive force compensation coefficient in the motor control process. Therefore, in step 3, based on the PID control strategy, the back-electromotive force compensation coefficient n, the value range of n is 0 to 1, and when n is 0.3, the response speed of the motor is the fastest.

[0112] Write the optimization program in the m file as follows:

[0113]

[0114]

[0115] When the back electromotive force compensation coefficient is different, the motor speed step response curve is as follows: Figure 8 As shown in the figure, a comprehensive analysis of the motor response speed and overshoot values shows that the optimal value is when the back electromotive force compensation coefficient is 0.3.

[0116] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

[0117] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the scope of protection of the present invention.

Claims

1. A method for quickly selecting a back electromotive force compensation coefficient during motor control, characterized in that: The method comprises the following steps: Step 1: Establish a typical motor control mathematical model based on the motor type; Step 2: Select any control method to establish a control strategy method model to achieve control of the inner loop and outer loop of the motor, where the inner loop is the current loop and the outer loop is the speed loop; Step 3: Add back-EMF compensation to the typical motor control mathematical model to establish a complete motor speed control mathematical model, analyze the impact of back-EMF compensation on the speed control of the motor in the motor speed control mathematical model, and identify the optimal back-EMF compensation coefficient through a cyclic simulation test in the motor speed control mathematical model.

2. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 1, wherein: In step 1, the selected parameters of the typical motor control mathematical model include voltage, flux linkage and torque.

3. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 2, wherein: In step 1, the expression of the typical motor control mathematical model established is: Where U is the power supply voltage (V), R is the motor resistance (Ω), L is the motor inductance (H), E is the motor back electromotive force (V), i is the motor control current (A), and k e is the motor back electromotive force coefficient (V·s / rad), ω is the motor speed (rad / s), T e is the electromagnetic torque of the motor (Nm), k t is the motor torque coefficient (Nm / A), T L is the motor load torque (Nm), J is the motor moment of inertia (kg·m 2 ), t is the time scale (s).

4. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 1, wherein: In step 2, the ADRC control strategy is selected to realize the control of the current loop and speed loop of the motor. The ADRC mainly consists of a tracking differentiator TD, an extended state observer ESO, and a nonlinear state error feedback control law SEF.

5. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 3, wherein: The control steps of the ADRC control strategy are as follows: Step 2-1: Current loop control strategy: First, establish the extended state observer; Performing Laplace transform on the voltage equation of formula (1) yields the current loop control object model: Convert equation (2) into state equation (3): in, Treat x2=f(x1,ω(t),t) as a new unknown state variable and add it to the original system of formula (3). That is, a new state is expanded on the basis of the state of the original system of formula (3). The original system of formula (3) becomes a linear system: A nonlinear state observer ESO is established for this system: Among them, ε1 is the observation error value, z1 is the first state observed, z2 is the second state observed, β 01i =2ω oi ,ω oi =3ω ci ,ω ci The current loop bandwidth is 1500Hz. Then calculate the feedback control law parameters, according to the empirical formula, k pi =ω ci ; Step 2-2: Speed loop control strategy: Similar to the current loop, analyze the values of the parameters in the speed loop ADRC. Speed loop bandwidth ω cv Take 500Hz, ω ov =3ω cv , β 01v =2ω ov 、 k pv =ω cv .

6. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 5, wherein: In step 3, based on the ADRC control strategy, the back electromotive force compensation coefficient n, the value range of n is 0 to 1, n is a variable, and when n is closer to 1, the response speed of the motor is faster.

7. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 3, wherein: In step 2, a PID control strategy is selected to control the current loop and speed loop of the motor.

8. The method for quickly selecting a back electromotive force compensation coefficient during motor control according to claim 7, wherein: The control steps of the PID control strategy are as follows: Step 2-1: Current loop control strategy; The current loop controller uses a parallel PI controller: Current loop controlled object model: The current loop system model is: make The current loop system model is simplified as: Where: k pi =ω i L, k ii =ω i R,ω i =1500rad / s,ω i is the current loop bandwidth; Step 2-2: Speed loop control strategy; The speed loop parameters are calculated in the same way as the current loop, k pv =2ω v J / k t , ω v =250rad / s,ω v is the speed loop bandwidth.

9. The method for quickly selecting a back electromotive force compensation coefficient in a motor control process according to claim 1, characterized in that: In the step 3, based on the PID control strategy, the back electromotive force compensation coefficient n has a value range of 0 to 1. When n is 0.3, the motor has the fastest response speed.

10. The method for quickly selecting a back electromotive force compensation coefficient in a motor control process according to claim 1, characterized in that: In step 3, the optimal back-electromotive force compensation coefficient is identified through cyclic simulation, specifically including taking the back-electromotive force compensation coefficient as a variable, writing an optimal coefficient selection program, and obtaining the value of the optimal back-electromotive force compensation coefficient in the motor control process.

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