CN116317771A - Position-sensor-free control method for low-speed and high-speed switching of permanent magnet synchronous motor - Google Patents

Position-sensor-free control method for low-speed and high-speed switching of permanent magnet synchronous motor Download PDF

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CN116317771A
CN116317771A CN202310137201.5A CN202310137201A CN116317771A CN 116317771 A CN116317771 A CN 116317771A CN 202310137201 A CN202310137201 A CN 202310137201A CN 116317771 A CN116317771 A CN 116317771A
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speed
switching
frequency voltage
omega
pulse vibration
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彭思齐
彭鸿羽
彭东琨
郭旦
李伟俊
陈思溢
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Xiangtan University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/0007—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using sliding mode control
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/13—Observer control, e.g. using Luenberger observers or Kalman filters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/18—Estimation of position or speed
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/22—Current control, e.g. using a current control loop
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/24—Vector control not involving the use of rotor position or rotor speed sensors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/022—Synchronous motors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters
    • H02P27/08—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation
    • H02P27/12—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation pulsing by guiding the flux vector, current vector or voltage vector on a circle or a closed curve, e.g. for direct torque control
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation

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Abstract

The invention provides a position-sensor-free control method for low-speed and high-speed switching of a permanent magnet synchronous motor, which comprises the following steps: firstly, determining a switching area by measuring the accurate estimation upper limit and the accurate estimation lower limit of a pulse vibration high-frequency voltage injection method and a sliding mode observer method; dividing the switching area into a plurality of intervals, and measuring parameters corresponding to each interval; substituting the measured parameters into an objective function and solving the optimal weight coefficient of each interval by using an improved particle swarm algorithm; and the motor operates to determine the corresponding optimal weight coefficient by comparing the rotation speed estimated values of the pulse vibration high-frequency voltage injection method corresponding to each interval endpoint, calculate the rotation speed and the rotor position in the switching process, and finish smooth low-high-speed switching. The invention can realize smooth transition of switching between the pulse vibration high-frequency injection voltage method and the sliding mode observer method, so that the system is more stable. Meanwhile, the conjugate gradient method is combined on the basis of the particle swarm algorithm, so that the local convergence capacity of the particle swarm algorithm is stronger, and the convergence speed is faster.

Description

Position-sensor-free control method for low-speed and high-speed switching of permanent magnet synchronous motor
Technical Field
The invention belongs to the field of permanent magnet synchronous motor control, and particularly relates to a method for mutually switching between a pulse vibration high-frequency signal injection method suitable for a low-speed domain and a sliding mode observer method suitable for a medium-high speed domain.
Background
The permanent magnet synchronous motor (Permanent Magnet Synchronous Motor, PMSM) has the characteristics of simple structure, small occupied space, high power density and high efficiency, so that the permanent magnet synchronous motor is widely applied to occasions with high precision and high dynamic performance requirements, such as electric automobiles in the automobile industry, cranes and lifters in the building industry and pumping units in the petroleum industry. Compared with asynchronous motor, the said motor has the features of high power factor, measurable rotor parameter, excellent control performance, etc. However, because the cost is high, in order to reduce the cost, the rotor position information and the rotating speed information of the permanent magnet synchronous motor are estimated through a control algorithm without a position sensor to replace the traditional mechanical sensor to realize the double closed-loop vector control strategy of the permanent magnet synchronous motor, and the problems of complex installation, easy external interference, high cost, limited application environment and the like caused by the mechanical sensor can be effectively solved. Therefore, sensorless control of the permanent magnet synchronous motor is gradually becoming a popular direction of research by a plurality of scholars.
Sensorless control of permanent magnet synchronous motors can be broadly divided into two categories depending on the applicable rotational speed domain: the first type is a high-frequency signal injection method based on salient pole characteristics of a motor, and the common methods are as follows: pulse high-frequency voltage injection, rotation high-frequency voltage injection, high-frequency square wave injection, etc.; the second type is a model method based on back electromotive force, and the following are commonly used: a sliding mode observer method, a model reference self-adaptive method, a disturbance observer method and the like. According to the mathematical model of the permanent magnet synchronous motor, the counter electromotive force is known to be related to the electric angular velocity, so that the counter electromotive force is obvious only at medium and high speeds, and is beneficial to observation and extraction, and therefore, a model method of the counter electromotive force is often adopted at the medium and high speeds. The prior art is mature and commonly used and comprises a sliding mode observer method, a model reference self-adaption, a Kalman filter and the like.
However, the control method of the low-speed domain and the high-speed domain has limitations, and accurate estimation can be realized only in the corresponding speed interval. In order to realize the full-speed domain sensorless control of the permanent magnet synchronous motor, a switching method is required to combine a control method of a low-speed domain with a control method of a medium-high speed domain to realize the full-speed domain sensorless control. The switching method adopted herein is directed to a pulse vibration high-frequency voltage injection method and a sliding mode observer method. Common switching methods are hysteresis switching and linear weighted switching. The hysteresis switching structure is simple and easy to realize, but the switching method is directly changed from one method to another method in a switching area, so that the estimation error of the rotating speed in the switching area is larger, and the system instability is easy to cause. Considering that the pulse vibration high-frequency signal injection method and the sliding mode observer method have different accuracy on rotor position estimation, the direct switching is easy to cause sudden increase or sudden decrease of errors, so that the system is easy to be unstable and even the system is easy to collapse. In order to realize smooth switching of the two control methods in the rotational speed switching region, some scholars propose to add a weight coefficient to the rotational speed and the rotor position estimated by the two control methods, and the estimated value in the switching region is obtained by weighting the estimated values estimated by the two methods, namely the weighted switching method. However, the simple linear change of the weight coefficient in the switching region cannot ensure that the estimated error variance is minimum when the two methods are switched, and step mutation can possibly occur in the rotating speed of the motor. In order to solve the above problems, a variable weight coefficient switching strategy based on particle swarm and conjugate particle swarm algorithm is proposed herein, so that the switching is smoother, and the motor is more stable in the switching area.
Disclosure of Invention
Aiming at the problems of unsmooth switching process and unstable system in the control of a full-speed domain permanent magnet synchronous motor without a position sensor by using a pulse vibration high-frequency voltage injection method and a sliding mode observer method at present, the variable weight coefficient method based on a conjugate particle swarm algorithm is provided, so that the switching between the pulse vibration high-frequency voltage injection method and the sliding mode observer method is smoother, the estimation precision in a switching area is more accurate, and the system is more stable.
The technical scheme provided by the invention is as follows:
step 1: the method comprises the steps of determining the accurate estimation lower limit omega of the rotating speed of a pulse vibration high-frequency voltage injection method m1 And accurately estimating the upper limit omega m2 Determining the accurate estimation lower limit omega of the rotating speed of the sliding mode observer method h1 And accurately estimating the upper limit omega h2 Finally, determining the switching area of the pulse vibration high-frequency voltage injection method and the sliding mode observer method as omega h1 -ω m2 ；
Step 2: setting the actual rotation speed of the permanent magnet synchronous motor in a switching area omega h1 -ω m2 Measuring the estimated rotating speed and rotor position of the corresponding pulse vibration high-frequency voltage injection method and the rotating speed and rotor position estimated by a sliding mode observer method, and dividing the rotating speed and rotor position into a plurality of sections for measurement;
step 3: substituting the data of each interval measured in the step 2 into an objective function, and then calculating the objective function by improving a particle swarm algorithm to ensure that each interval is fitted to obtain a corresponding optimal weight coefficient lambda 1 、λ 2 And records it;
step 4: when the permanent magnet synchronous motor operates, the optimal weight coefficient corresponding to each section in the switching section can be obtained through the comparator, and is substituted into the rotating speed estimation type of the switching section to obtain the accurate estimation at the moment, and finally smooth transition between the pulse vibration high-frequency voltage injection method and the sliding mode observer method is realized.
Further, ω of the switching region in step 1 h1 -ω m2 The upper and lower limits have the following requirements:
firstly, the minimum rotating speed of an algorithm switching area is required to reach the lower rotating speed limit accurately estimated by a sliding mode observer method, and then the maximum rotating speed of the switching area is required to be lower than the upper rotating speed limit accurately estimated by a pulse vibration high-frequency voltage injection method, namely the pulse vibration high-frequency voltage injection method and the sliding mode observer method in the switching area are required to be accurately estimated.
Further, the step 2 includes the steps of:
determining a switching area omega according to the upper rotating speed limit accurately estimated by the pulse vibration high-frequency voltage injection method and the lower rotating speed limit accurately estimated by the sliding mode observer method measured in the step 1 h1 -ω m2 Lower limit omega of (2) h1 And an upper limit omega m2 Then taking 0.1 as the length of one measurement interval, and taking omega h1 -ω m2 Is divided into
Figure BDA0004086363650000021
In each 0.1 interval, ten measuring points of 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09 and 0.1 are taken, if in omega h1 -ω h1 Omega is taken in the above-described manner within the +0.1 interval h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1 ten measurement points, the actual rotation speed is set to ω h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1, respectively measuring the estimation value of the corresponding pulse vibration high-frequency voltage method and the estimation value of the sliding mode observer method, and recording the actual rotating speed of the right end point of the interval as omega h1 The estimated value of pulse vibration high-frequency voltage method at +0.1 and the like are always measured>
Figure BDA0004086363650000022
An estimated value of the pulse-vibration high-frequency voltage method of each section, an estimated value of the sliding-mode observer method, and an estimated value of the pulse-vibration high-frequency voltage method of the right end point of each section.
In one step, the objective function described in step 3 is:
Figure BDA0004086363650000023
s.t.λ 1 +λ 2 ＝1
0≤λ 1 ≤1
0≤λ 2 ≤1
omega in the above ei And theta ei For the actual rotational speed and rotor position of the permanent magnet synchronous motor,
Figure BDA0004086363650000031
and->
Figure BDA0004086363650000032
The rotational speed estimation values of a pulse vibration high-frequency voltage injection method and a sliding mode observer method are respectively obtained. />
Figure BDA0004086363650000033
And->
Figure BDA0004086363650000034
Rotor position estimation values of a pulse vibration high-frequency voltage injection method and a sliding mode observer method are respectively obtained. Lambda (lambda) 1 And lambda (lambda) 2 The weight coefficient to be solved is obtained. Substituting the rotation speed and the rotor position estimated value of each interval measured in the step 2 into the above formula to obtain the objective function which can be solved by us.
Further, the improved particle swarm algorithm described in step 3 comprises the steps of:
the first step of initializing the initial population total number N of the particle swarm, the random position Xi and the speed Vi of each particle, and the iteration times T l The method comprises the steps of carrying out a first treatment on the surface of the Step two, obtaining the fitness value of each particle through an objective function; thirdly, comparing the fitness value of each particle with the fitness value of the best position pbest passed by the individual, and if the fitness value is better, taking the fitness value as the current best position pbest of the individual; step four, comparing the adaptation value of each particle with the adaptation value of the best position gbest passed by the group, and if the adaptation value is better, taking the particle as the current best position gbest of the group; fifth, the velocity and position of the particles are adjusted by updating the formula:
v i ＝v i +c 1 ×rand()×(pbest i -x i )+c 2 ×rand()×(gbest i -x i )
x i ＝x i +v i
wherein v is i Represents the velocity of the ith particle (i=1, 2, n.), x i Representing the position of the ith particle, rand () is a random number between 0 and 1, c 1 、c 2 Is a learning factor with a value of 2, pbest i Indicating the best position, gbest, found by the i-th particle itself traversal i Traversing the found best locations for all particles; sixth step, the obtained gbest i Updating by using conjugate gradient method to obtain optimal solution to replace gbest i The method comprises the following specific steps:
let k=0, t first g For the number of iterations, gbest is taken i Denoted as x 0 Calculating a gradient
Figure BDA0004086363650000035
Then calculating correction coefficients and search directions:
Figure BDA0004086363650000036
Figure BDA0004086363650000037
wherein beta is k-1 To correct the coefficient d k Is the search direction; step a is then determined using a linear search method k The method comprises the steps of carrying out a first treatment on the surface of the Then iterate with the following iterative formula and calculate the gradient g k+1 ：
x k+1 ＝x k +a k d k
Figure BDA0004086363650000041
Finally judging whether the iteration times are T g Is then finally obtainedThe optimal value of the gbest is assigned i If not, the method returns to calculate the correction coefficient and the search direction to continue the loop. Seventh step, judging whether the iteration number is T l If not, returning to the second step, and outputting the gbest at the moment i 。
Further, the specific content and details of the comparison in the comparator described in step 4 are:
in step 2, the estimated value of pulse vibration high-frequency voltage injection method of the upper limit and the lower limit of each corresponding section is detected by setting the actual rotation speed of the motor, and in step 3, the optimal weight coefficient lambda of each section is calculated 1 、λ 2 In the running process of the permanent magnet synchronous motor, the estimated value of the pulse vibration high-frequency voltage injection method is compared with the upper limit and the lower limit of each section, so that the section in which the estimated value is located can be known, the optimal weight coefficient of the section can be also known, and the optimal weight coefficient is substituted into the following estimated formula:
Figure BDA0004086363650000042
Figure BDA0004086363650000043
wherein the method comprises the steps of
Figure BDA0004086363650000044
Is->
Figure BDA0004086363650000045
Estimated rotational speed and estimated rotor position obtained by multiplying the weight coefficients for pulse-oscillation high-frequency voltage injection method and sliding-mode observer method, +.>
Figure BDA0004086363650000046
And->
Figure BDA0004086363650000047
Rotational speed estimation values of pulse vibration high-frequency voltage injection method and sliding mode observer method respectively, < >>
Figure BDA0004086363650000048
And->
Figure BDA0004086363650000049
Rotor position estimation values of a pulse vibration high-frequency voltage injection method and a sliding mode observer method are respectively obtained.
An accurate estimate of the rotational speed and rotor position of the permanent magnet synchronous motor at this time can be obtained.
The beneficial effects are that:
1. the pulse vibration high-frequency voltage injection method and the sliding mode observer method can be switched more smoothly, and the system is more stable.
2. Compared with the traditional weighted switching method which may cause buffeting phenomenon in the running process of the permanent magnet synchronous motor, the method disclosed by the invention has the advantages that the estimated rotating speed and rotor position are more accurate, and the phenomenon can be restrained.
3. The method adopted by the invention is not affected by the actual load change, and the estimation precision can be ensured under the condition of sudden load in the actual operation process.
4. The invention adopts the steps of firstly calculating the optimal weight value of each interval in the switching area, then directly determining the optimal weight by comparing the estimated values of the pulse vibration high-frequency voltage method in the running process of the motor, so that the rotating speed and the rotor position can be estimated more quickly when the motor runs, and the running fluency of the motor is ensured.
Drawings
FIG. 1 is a flow chart of an improved particle swarm algorithm.
Fig. 2 is a diagram of a low-high speed switching control system of a permanent magnet synchronous motor.
Fig. 3 is a diagram of a comparator structure.
The specific embodiment is as follows:
the invention will be further described in detail with reference to the drawings and examples.
The invention discloses a position-sensor-free control method for low-speed and high-speed switching of a permanent magnet synchronous motor, which comprises the following steps of:
step one: actual practice is that ofMeasuring the rotation speed of pulse vibration high-frequency voltage injection method of permanent magnet synchronous motor and accurately estimating the lower limit omega m1 Accurate estimation of the upper limit omega m2 And the rotation speed of the sliding mode observer method to accurately estimate the lower limit omega h1 Accurate estimation of the upper limit omega h2 Then determining the switching region omega of the pulse vibration high-frequency voltage injection method and the sliding mode observer method according to the condition that the minimum rotating speed of the switching region reaches the lower rotating speed limit accurately estimated by the sliding mode observer method and the maximum rotating speed of the switching region is lower than the upper rotating speed limit accurately estimated by the pulse vibration high-frequency voltage injection method h1 -ω m2 ；
Step two: determining a switching area omega according to the upper rotating speed limit accurately estimated by the pulse vibration high-frequency voltage injection method and the lower rotating speed limit accurately estimated by the sliding mode observer method measured in the step 1 h1 -ω m2 Lower limit omega of (2) h1 And an upper limit omega h2 Then taking 0.1 as the length of one measurement interval, and taking omega h1 -ω m2 Is divided into
Figure BDA0004086363650000051
In each 0.1 interval, ten measuring points of 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09 and 0.1 are taken, if in omega h1 -ω h1 Omega is taken in the above-described manner within the +0.1 interval h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1 ten measurement points, the actual rotation speed is set to ω h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1, respectively measuring the estimated rotation speed and rotor position of the corresponding pulse vibration high-frequency voltage method and sliding mode observer method, and recording the actual rotation speed of the right end point of the interval as omega h1 The estimated value of pulse vibration high-frequency voltage method at +0.1 is recorded as M 1 And the like, the estimated value of pulse vibration high-frequency voltage method, the estimated value of sliding mode observer method and the estimated value of n intervals are always measuredM is recorded according to the estimated value of pulse vibration high-frequency voltage method at the right end point of each interval 0 (the estimated value of the pulse vibration high-frequency voltage method corresponding to the left end point of the first measurement interval), M 1 、M 2 、......、M n ；
Step three: substituting the estimated rotation speed and rotor position of the pulse vibration high-frequency voltage method and the sliding mode observer method of each section measured in the second step into the improved particle swarm algorithm shown in fig. 1 to obtain the optimal weight coefficient of each section. The objective function of the improved particle swarm algorithm is:
Figure BDA0004086363650000052
s.t.λ 1 +λ 2 ＝1
0≤λ 1 ≤1
0≤λ 2 ≤1
wherein omega ei And theta ei For the actual rotational speed and rotor position of the permanent magnet synchronous motor,
Figure BDA0004086363650000053
and->
Figure BDA0004086363650000054
Rotational speed estimation values of pulse vibration high-frequency voltage injection method and sliding mode observer method respectively, < >>
Figure BDA0004086363650000055
And->
Figure BDA0004086363650000056
Rotor position estimation values, lambda, of pulse vibration high-frequency voltage injection method and sliding mode observer method respectively 1 And lambda (lambda) 2 The weight coefficient to be solved is obtained. The specific steps of the improved particle swarm algorithm are as follows:
the first step of initializing the initial population total number N of the particle swarm, the random position Xi and the speed Vi of each particle, and the iteration times T l The method comprises the steps of carrying out a first treatment on the surface of the Step two, the fitness of each particle is obtained through an objective functionValue, value; thirdly, comparing the fitness value of each particle with the fitness value of the best position pbest passed by the individual, and if the fitness value is better, taking the fitness value as the current best position pbest of the individual; step four, comparing the adaptation value of each particle with the adaptation value of the best position gbest passed by the group, and if the adaptation value is better, taking the particle as the current best position gbest of the group; fifth, the velocity and position of the particles are adjusted by updating the formula:
v i ＝v i +c 1 ×rand()×(pbest i -x i )+c 2 ×rand()×(gbest i -x i )
x i ＝x i +v i
wherein v is i Represents the velocity of the ith particle (i=1, 2, n.), x i Representing the position of the ith particle, rand () is a random number between 0 and 1, c 1 、c 2 Is a learning factor with a value of 2, pbest i Indicating the best position, gbest, found by the i-th particle itself traversal i Traversing the found best locations for all particles; sixth step, the obtained gbest i Updating by using conjugate gradient method to obtain optimal solution to replace gbest i The method comprises the following specific steps:
let k=0, t first g For the number of iterations, gbest is taken i Denoted as x 0 Calculating a gradient
Figure BDA0004086363650000061
Then calculating correction coefficients and search directions:
Figure BDA0004086363650000062
Figure BDA0004086363650000063
wherein beta is k-1 To correct the coefficient d k Is the search direction; step a is then determined using a linear search method k The method comprises the steps of carrying out a first treatment on the surface of the Then iterate with the following iterative formula and calculate the gradient g k+1 ：
x k+1 ＝x k +a k d k
Figure BDA0004086363650000064
Finally judging whether the iteration times are T g The final optimal value is assigned to the gbest i If not, returning to calculating the correction coefficient and searching the direction to continue circulation; seventh step, judging whether the iteration number is T l If not, returning to the second step, and outputting the gbest at the moment i . Gbest at this time i The optimal weight coefficient of each section is obtained and recorded by a conjugate particle swarm algorithm.
Step four: and editing the measured data in the second and third steps into a comparator shown in fig. 3, and then realizing full-speed domain control of the permanent magnet synchronous motor through a low-speed and high-speed switching control system of the permanent magnet synchronous motor shown in fig. 2. The whole control principle is shown in figure 2, a rotating speed ring and a current ring are designed, and a high-frequency voltage signal is injected into the d-axis of an estimated rotating coordinate system
Figure BDA0004086363650000065
Three-phase voltage is output to an embedded permanent magnet synchronous motor (IPSM) through inverse park transformation, space Vector Pulse Width Modulation (SVPWM) and an inverter, then three-phase current and three-phase voltage obtained through sampling are output to a pulse vibration high-frequency voltage injection method and a sliding mode observer method through park transformation for estimation, and then the position of a rotor estimated by the pulse vibration high-frequency voltage is estimated>
Figure BDA0004086363650000071
Rotational speed->
Figure BDA0004086363650000072
And the rotor position estimated by sliding mode observer method +.>
Figure BDA0004086363650000073
Rotational speed->
Figure BDA0004086363650000074
And the optimal weight coefficient output by the comparator is input to a rotor position and speed estimation module with the following formula:
Figure BDA0004086363650000075
Figure BDA0004086363650000076
and obtaining the weighted estimated rotor position and the weighted estimated rotating speed, and outputting the weighted estimated rotor position and the weighted estimated rotating speed to complete closed-loop control.
In summary, the scheme provided by the invention can enable the pulse vibration high-frequency voltage injection method and the sliding mode observer method to cut back and forth more smoothly, so that the motor operates more stably. Hardly influenced by load mutation in the actual operation process, and has stronger anti-interference capability. And the buffeting phenomenon generated by the linear weighted switching method can be eliminated, so that the whole control system is more stable. And the particle swarm algorithm is improved, a conjugate gradient method is added, and the local searching capability of the algorithm is enhanced.

Claims (6)

1. The control method without the position sensor for the low-speed and high-speed switching of the permanent magnet synchronous motor is characterized by comprising the following steps of:
step 1: the method comprises the steps of determining the accurate estimation lower limit omega of the rotating speed of a pulse vibration high-frequency voltage injection method m1 And accurately estimating the upper limit omega m2 Determining the accurate estimation lower limit omega of the rotating speed of the sliding mode observer method h1 And accurately estimating the upper limit omega h2 Finally, determining the switching area of the pulse vibration high-frequency voltage injection method and the sliding mode observer method as omega h1 -ω m2 ；
Step 2: setting the actual rotation speed of the permanent magnet synchronous motor in a switching area omega h1 -ω m2 In the inner part of the inner part,measuring the estimated rotating speed and rotor position of the corresponding pulse vibration high-frequency voltage injection method and the rotating speed and rotor position estimated by a sliding mode observer method, and dividing the rotating speed and rotor position into a plurality of intervals for measurement;
step 3: substituting the data of each interval measured in the step 2 into an objective function, and then calculating the objective function by improving a particle swarm algorithm to ensure that each interval is fitted to obtain a corresponding optimal weight coefficient lambda 1 、λ 2 And records it;
step 4: when the permanent magnet synchronous motor operates, the optimal weight coefficient corresponding to each section in the switching section can be obtained through the comparator, and is substituted into the rotating speed and rotor position estimation type of the switching section to obtain the accurate estimation at the moment, and finally smooth transition between the pulse vibration high-frequency voltage injection method and the sliding mode observer method is realized.
2. The method for controlling a position-less sensor for switching a permanent magnet synchronous motor at a low speed according to claim 1, wherein said step 1 switches a region ω h1 -ω m2 The selection of (2) has the following requirements:
firstly, the minimum rotating speed of an algorithm switching area is required to reach the lower rotating speed limit accurately estimated by a sliding mode observer method, and then the maximum rotating speed of the switching area is required to be lower than the upper rotating speed limit accurately estimated by a pulse vibration high-frequency voltage injection method, namely the pulse vibration high-frequency voltage injection method and the sliding mode observer method in the switching area are required to be accurately estimated.
3. The method for controlling the permanent magnet synchronous motor without the position sensor for switching at a low speed according to claim 1, wherein the measuring method of the step 2 comprises the following steps:
determining a switching area omega according to the upper rotating speed limit accurately estimated by the pulse vibration high-frequency voltage injection method and the lower rotating speed limit accurately estimated by the sliding mode observer method measured in the step 1 h1 -ω m2 Lower limit omega of (2) h1 And an upper limit omega m2 Then taking 0.1 as the length of one measurement interval, and taking omega h1 -ω m2 Is divided into
Figure QLYQS_1
In each 0.1 interval, ten measuring points of 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09 and 0.1 are taken, if in omega h1 -ω h1 Omega is taken in the above-described manner within the +0.1 interval h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1 ten measurement points, the actual rotation speed is set to ω h1 +0.01、ω h1 +0.02、ω h1 +0.03、ω h1 +0.04、ω h1 +0.05、ω h1 +0.06、ω h1 +0.07、ω h1 +0.08、ω h1 +0.09、ω h1 +0.1, respectively measuring the estimated rotation speed and rotor position of the corresponding pulse vibration high-frequency voltage method and sliding mode observer method, and recording the actual rotation speed of the right end point of the interval as omega h1 The estimated value of pulse vibration high-frequency voltage method at +0.1 is recorded as M 1 And recording M by analogy with the estimated value of the pulse vibration high-frequency voltage method, the estimated value of the sliding mode observer method and the estimated value of the pulse vibration high-frequency voltage method at the right end point of each interval after n intervals are measured all the time 0 (the estimated value of the pulse vibration high-frequency voltage method corresponding to the left end point of the first measurement interval), M 1 、M 2 、......、M n . The length of the measurement section may be 0.01, 0.001, 0.0001, or the like.
4. The method for controlling the permanent magnet synchronous motor without the position sensor according to claim 1, wherein the objective function in the step 3 is:
Figure QLYQS_2
s.t.λ 1 +λ 2 ＝1
0≤λ 1 ≤1
0≤λ 2 ≤1。
5. the method for controlling the position-less sensor of the low-speed switching of the permanent magnet synchronous motor according to claim 1, wherein the conjugate particle swarm algorithm of the step 3 comprises the following steps:
the first step of initializing the initial population total number N of the particle swarm, the random position Xi and the speed Vi of each particle, and the iteration times T l ；
Step two, obtaining the fitness value of each particle through an objective function;
thirdly, comparing the fitness value of each particle with the fitness value of the best position pbest passed by the individual, and if the fitness value is better, taking the fitness value as the current best position pbest of the individual;
step four, comparing the adaptation value of each particle with the adaptation value of the best position gbest passed by the group, and if the adaptation value is better, taking the particle as the current best position gbest of the group;
fifth, the velocity and position of the particles are adjusted by updating the formula:
v i ＝v i +c 1 ×rand()×(pbest i -x i )+c 2 ×rand()×(gbest i -x i )
x i ＝x i +v i
sixth step, the obtained gbest i Updating by using conjugate gradient method to obtain optimal solution to replace gbest i The method comprises the following specific steps:
let k=0, t first g For the number of iterations, gbest is taken i Denoted as x 0 Calculating a gradient
Figure QLYQS_3
Then calculating correction coefficients and search directions:
Figure QLYQS_4
Figure QLYQS_5
then iterate with the following iterative formula and calculate the gradient g k+1 ：
x k+1 ＝x k +a k d k
Figure QLYQS_6
Finally judging whether the iteration times are T g The final optimal value is assigned to the gbest i If not, the method returns to calculate the correction coefficient and the search direction to continue the loop. Seventh step, judging whether the iteration number is T l If not, returning to the second step, and outputting the gbest at the moment i 。
6. The method for controlling the permanent magnet synchronous motor without the position sensor according to claim 1, wherein the rotation speed and the rotor position estimation formula in the step 4 are as follows:
Figure QLYQS_7
Figure QLYQS_8
。
CN202310137201.5A 2023-02-20 2023-02-20 Position-sensor-free control method for low-speed and high-speed switching of permanent magnet synchronous motor Pending CN116317771A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116756513A (en) * 2023-07-05 2023-09-15 大庆石油管理局有限公司 Tower type oil pumping machine data filtering algorithm

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116756513A (en) * 2023-07-05 2023-09-15 大庆石油管理局有限公司 Tower type oil pumping machine data filtering algorithm
CN116756513B (en) * 2023-07-05 2024-02-13 大庆石油管理局有限公司 Tower type oil pumping machine data filtering algorithm

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