CN107425781A - A kind of SRM positions predictor method based on linear flux linkage model and linear regression analysis - Google Patents
A kind of SRM positions predictor method based on linear flux linkage model and linear regression analysis Download PDFInfo
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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
- H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
- H02P23/14—Estimation or adaptation of motor parameters, e.g. rotor time constant, flux, speed, current or voltage
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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
- 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
- H02P25/08—Reluctance motors
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Abstract
The invention discloses a kind of SRM positions predictor method based on linear flux linkage model and linear regression analysis.This method only needs the flux linkage characteristic data at any two rotor-position in linear zone, so as to obtain the magnetic linkage value at two end points of linear zone, and as reference.Detection conducting phase voltage, current value, are calculated magnetic linkage value.If the value shows that rotor-position is located at linear zone between two Reference Stator Flux Linkage values, then carry out position with linear flux linkage model and estimate.Otherwise, show that rotor-position is located at inelastic region, on the premise of assuming that motor speed is constant in the short time, linear regression analysis is carried out to linear zone position data and sampling sequence number, and then for being estimated to inelastic region rotor-position.Such as need further to reduce the accumulated error in single-phase estimate, multiphase flux linkage characteristic can be used to replace single-phase flux linkage characteristic to carry out position and estimated.This method precision is high, be easily achieved, applicability is good, and can avoid or reduce alternate mutual inductance and the influence of magnetic circuit saturation.
Description
Technical Field
The invention relates to a Switched Reluctance Motor (SRM) accurate position estimation method based on a linear flux linkage model and linear regression analysis, and belongs to the field of motor position sensorless control.
Background
The position information is the basis for the operation of the switched reluctance motor. Typically, the position information is obtained by mechanical position sensors, such as rotary transformers, hall sensors, photoelectric encoders, and the like. However, not only do these mechanical position sensors add cost and complexity to the drive system, but their accuracy and reliability are susceptible to environmental factors such as temperature, dust, and vibration. Therefore, it is necessary to develop a position sensorless control method with low cost, high accuracy and high reliability.
In order to implement position sensorless control, researchers have proposed a number of position estimation methods. These methods are mainly divided into two categories: one is a non-conduction phase position estimation method, and the other is a conduction phase position estimation method.
The first method is to inject high-frequency voltage pulses into a non-excited phase, detect the amplitude or rise time of current to determine the inductance value of an unsaturated region, and further obtain the position value or the region of a rotor. The disadvantages of this type of process are: when there is current in other phases, the current of the pulse injected phase may be affected by other mutual inductance; the non-conducting phase injected pulse current may generate negative torque; furthermore, at high speeds, the excitation current waveform accounts for a significant portion of the entire phase cycle, limiting the time of pulse injection. Therefore, the method is only suitable for starting and low-speed working conditions.
The second method estimates the rotor position mainly according to the measured excitation phase voltage and current value through a lookup table, a mathematical model, an observer or an intelligent algorithm and the like. This type of approach has the advantage of not creating extra power consumption nor requiring additional hardware. However, most of the existing conduction phase position estimation methods need magnetic linkage characteristic data of all or many rotor positions, difficulty and workload of data acquisition and processing are increased, and a large storage space is often needed. In addition, the estimation precision of the method is easily influenced by the interphase mutual inductance and the magnetic field saturation.
Disclosure of Invention
The invention divides the relation curve of the phase flux linkage and the rotor position of the switched reluctance motor into two areas, and respectively adopts a linear flux linkage model and linear regression analysis to estimate the rotor position aiming at different areas. The technical scheme is as follows:
the method comprises the following steps: in the relation curve of the phase flux linkage and the rotor position of the switched reluctance motor, an interval [ theta ] is divided1,θhr]The linear region is defined, and the remaining region is the nonlinear region. Theta1And thetahrCan be obtained from the formulae (1) and (2).
θ1＝θa-(βs+βr)/2 (1)
θhr＝θa-βr/2 (2)
Wherein, thetaa、βsAnd βrRespectively a pair of electric motorsA uniform position, a stator pole arc, and a rotor pole arc.
Obtaining any two rotor positions theta in a linear regionxAnd thetayMagnetic linkage characteristic data psixAnd psiyAnd acquiring flux linkage characteristics at two end points of a linear region through an equation (3), wherein psi is phase flux linkage, theta is a rotor position, and meanwhile, obtaining an analytic expression of the phase flux linkage and the phase current at the end points through fitting.
Step two: detecting the conducting phase voltage and current value, and acquiring the flux linkage value psi at the end point of the linear region by using the analytical expression of the flux linkage and the phase current obtained in the previous step1And psihrAnd set as the reference flux linkage.
The phase flux linkage value at this time is calculated by equation (4).
Where ψ (0) is an initial flux linkage, and u, i, and r are phase voltage, phase current, and phase resistance of the switched reluctance motor, respectively.
Step three: if psi1≤ψ≤ψhrAnd if the rotor position is in the linear region, the rotor position angle can be obtained through a linear flux linkage model, as shown in formula (5).
Step four: if it does not satisfy psi1≤ψ≤ψhrThe rotor position is in the non-linear area, and the linear area position data and the sampling serial number are processed on the premise of assuming that the rotating speed of the motor is constant in a short timeAnd (3) linear regression analysis, namely determining the coefficient of the unary linear regression function shown in the formula (6) and further predicting the position of the rotor in the nonlinear region.
Wherein,is an estimated value of the rotor position at the kth sampling point, and k is the sampling point serial number. As a coefficient, it can be calculated from equation (7) based on the data of the linear region.
Wherein, thetakIs the rotor position value at the kth sampling point in the linear region.
Step five: if the accumulated error introduced during the estimation of the position of the rotor in the non-linear region needs to be further reduced, the estimation can be carried out by adopting the multi-phase flux linkage characteristic instead of the single-phase flux linkage characteristic. The phase selection principle is as follows: and the nonlinear area of each phase is utilized to shorten the nonlinear area of single-phase estimation.
The invention has the beneficial effects that: the method is simple and easy to realize. By adopting a simple linear model, only the flux linkage characteristic data at two rotor positions are needed, and only a small amount of physical memory is needed; high precision and strong robustness. The linear region flux linkage characteristic has high resolution and low sensitivity to flux linkage errors, and can effectively avoid interphase mutual inductance and reduce the influence of magnetic circuit saturation on the estimated result. In addition, the accumulated error is reduced by a multiphase estimation method; and the applicability is good. The method has good precision under the working conditions of angle position control, current chopping control and voltage PWM control, and is also suitable for different switched reluctance motor topologies.
Drawings
Fig. 1 is a graph showing a relationship between a single-phase flux linkage and a rotor position of a switched reluctance motor at a certain current.
Fig. 2 is a graph showing a relationship between a three-phase flux linkage and a rotor position of a three-phase switched reluctance motor under a certain current.
FIG. 3 is a flow chart of a method for estimating the position of an SRM based on a linear flux linkage model and linear regression analysis.
Detailed Description
The technical scheme of the invention is explained in detail in the following by combining the drawings and specific examples. The motor used in the example was a 1kW three-phase 12/8 pole switched reluctance motor.
The method comprises the following steps: in the relation curve of the single-phase flux linkage and the rotor position of the switched reluctance motor under a certain current shown in figure 1, a linear region [ theta ] is formed1,θhr]Define a linear region and the remaining region a non-linear region for the switched reluctance motor given by way of example, βs，βrAnd thetaa15 °,17 °, and 22.5 °, respectively. From the formulae (1) and (2), θ can be obtained1And thetahr6.5 deg. and 14 deg., respectively.
Flux linkage characteristic data of the switched reluctance motor at 7.5 degrees and 15 degrees can be conveniently obtained by using a torque balance test method, and because 15 degrees are close to 14 degrees, a linear region is selected from [6.5 degrees, 15 degrees ], and the rest is a nonlinear region. The flux linkage at 6.5 ° can be obtained from formula (8):
obtaining the magnetic linkage psi by fitting6.5°And psi15°Analytic expression psi with phase current i6.5°(i) And psi15°(i)。
Step two: detecting the conducting phase voltage and current values, and obtaining an analytic expression psi by utilizing the fitting of the previous step6.5°(i) And psi15°(i) Acquiring the flux linkage value psi at the end point of the linear region at the time6.5°(i*) And psi15°(i*) And is set as a reference flux linkage, where i*The phase current value at this time. Meanwhile, the flux linkage value ψ (i) at this time is calculated by equation (4)*)。
Step three: if psi6.5°(i*)≤ψ(i*)≤ψ15°(i*) If the rotor position is in the linear region, the rotor position angle can be obtained through the linear flux linkage model, as shown in formula (9).
Step four: if it does not satisfy psi6.5°(i*)≤ψ(i*)≤ψ15°(i*) When the rotor position is in the non-linear region, the coefficient is obtained by the equation (7) based on the linear region position data and the sampling point serial number obtained in the previous stepAndand the subsequent unitary linear regression function shown in the formula (6) is used for estimating the rotor positions at different sampling points in the nonlinear region.
Step five: in order to further reduce the accumulated error introduced during the estimation of the position of the nonlinear area, the three-phase flux linkage characteristic is adopted to replace the single-phase flux linkage characteristic for estimation. According to the selection principle, a phase selection strategy is formulated as shown in table 1.
In Table 1, #refFor a given reference flux linkage, psi is selected in this exampleref＝ψ6.5°. In addition, when the three-phase flux linkage values are all larger than psirefThe selected phase remains unchanged. In a relation curve of a three-phase flux linkage of the three-phase switched reluctance motor and a rotor position at a certain current shown in fig. 2, a thick solid line represents a portion estimated from each phase-coherent position determined according to table 1.
TABLE 1. phase selection strategy
In Table 1, #refFor a given reference flux linkage, psi is selected in this exampleref＝ψ6.5°. In addition, when the three-phase flux linkage values are all larger than psirefThe selected phase remains unchanged. In a relation curve of a three-phase flux linkage of the three-phase switched reluctance motor and a rotor position at a certain current shown in fig. 2, a thick solid line represents a portion estimated from each phase-coherent position determined according to table 1.
A flow chart of the SRM position estimation method based on the linear flux linkage model and the linear regression analysis is shown in fig. 3.
Claims (6)
1. A SRM position estimation method based on a linear flux linkage model and linear regression analysis is characterized by comprising the following steps: dividing a relation curve of a phase flux linkage and a rotor position of a Switched Reluctance Motor (SRM) into two regions, and respectively adopting a linear flux linkage model and linear regression analysis to estimate the rotor position aiming at different regions, wherein the position estimation method comprises the following implementation steps:
the method comprises the following steps: in the relation curve of the phase flux linkage and the rotor position of the switched reluctance motor, an interval [ theta ] is divided1,θhr]Defining as linear region, and obtaining as non-linear regionTwo endpoints theta of linear region1And thetahrObtaining an analytical expression of phase flux linkage and phase current at the end point through fitting according to the flux linkage characteristics;
step two: detecting the conducting phase voltage and current value, and acquiring the flux linkage value psi at the end point of the linear region by using the analytical expression of the flux linkage and the phase current obtained in the previous step1And psihrAnd setting as a reference flux linkage, and calculating a phase flux linkage value psi at the same time;
step three: if psi1≤ψ≤ψhrIf the rotor position is in the linear region, estimating the rotor position by using a linear flux linkage model;
step four: if it does not satisfy psi1≤ψ≤ψhrWhen the rotor position is in the nonlinear region, linear regression analysis is carried out on linear region position data and sampling serial numbers on the premise of assuming constant motor rotating speed in a short time, and coefficients of a unary linear regression function are determined and are further used for estimating the rotor position in the nonlinear region;
step five: if the accumulated error introduced during the estimation of the position of the rotor in the nonlinear area needs to be further reduced, the estimation can be carried out by adopting a multiphase flux linkage characteristic to replace a single-phase flux linkage characteristic, and the phase selection principle is as follows: and the nonlinear area of each phase is utilized to shorten the nonlinear area of single-phase estimation.
2. The SRM position estimation method based on the linear flux linkage model and the linear regression analysis as claimed in claim 1, wherein: two endpoints theta of the linear zone stated in the step one1And thetahrMay be represented by the formula θ1＝θa-(βs+βr) 2 and thetahr＝θa-βrCalculated as/2, where θa、βsAnd βrRespectively the aligned position of the motor, the stator pole arc and the rotor pole arc.
3. The SRM position estimation method based on the linear flux linkage model and the linear regression analysis as claimed in claim 1, wherein: step one saidTwo endpoints theta of linear region1And thetahrThe flux linkage characteristic of (A) is represented by the formulaCalculated where ψ is the flux linkage, θ is the rotor position, ψxAnd psiyIs any two rotor positions theta in a linear regionxAnd thetayFlux linkage characteristic data of (a).
4. The SRM position estimation method based on the linear flux linkage model and the linear regression analysis as claimed in claim 1, wherein: the phase flux linkage characteristic stated in the step two is through a formulaCalculated, where ψ (0) is an initial flux linkage, and u, i and r are phase voltage, phase current and phase resistance of the switched reluctance motor, respectively.
5. The SRM position estimation method based on the linear flux linkage model and the linear regression analysis as claimed in claim 1, wherein: the rotor position estimation based on the linear flux linkage model in the third step can be expressed as a formula
6. The SRM position estimation method based on the linear flux linkage model and the linear regression analysis as claimed in claim 1, wherein: the linear regression function described in step four can be expressed asWherein,for an estimated value of the rotor position at the kth sampling point, k being the sampling pointThe serial number of the serial number,as coefficients, can be based on data in the linear region, as formulated byIs calculated, wherein thetakIs the rotor position value at the kth sampling point in the linear region.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108429505A (en) * | 2018-03-01 | 2018-08-21 | 西北工业大学 | A kind of switched reluctance machines instantaneous torque on-line identification method |
| CN108875168A (en) * | 2018-06-04 | 2018-11-23 | 同济大学 | A kind of switched reluctance machines magnetic field Analytic Calculation Method considering saturation |
| CN109672386A (en) * | 2018-11-13 | 2019-04-23 | 江苏大学 | A kind of switch magnetoresistance motor rotor position detection method |
| CN110334386A (en) * | 2019-05-09 | 2019-10-15 | 深圳大学 | A kind of planar motor control method and terminal device based on parametric regression |
| CN110661467A (en) * | 2018-06-29 | 2020-01-07 | 北京自动化控制设备研究所 | Switched reluctance motor position estimation method based on flux linkage characteristic coordinate transformation |
| CN111190128A (en) * | 2018-11-15 | 2020-05-22 | 北京自动化控制设备研究所 | Detection algorithm for BH characteristics of ferromagnetic material of reluctance motor |
| CN112580209A (en) * | 2020-12-21 | 2021-03-30 | 湖南科技大学 | On-line torque estimation method of switched reluctance motor based on segmented analytical modeling |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108429505A (en) * | 2018-03-01 | 2018-08-21 | 西北工业大学 | A kind of switched reluctance machines instantaneous torque on-line identification method |
| CN108875168A (en) * | 2018-06-04 | 2018-11-23 | 同济大学 | A kind of switched reluctance machines magnetic field Analytic Calculation Method considering saturation |
| CN108875168B (en) * | 2018-06-04 | 2021-03-26 | 同济大学 | Switched reluctance motor magnetic field analysis calculation method considering saturation |
| CN110661467A (en) * | 2018-06-29 | 2020-01-07 | 北京自动化控制设备研究所 | Switched reluctance motor position estimation method based on flux linkage characteristic coordinate transformation |
| CN110661467B (en) * | 2018-06-29 | 2021-09-14 | 北京自动化控制设备研究所 | Switched reluctance motor position estimation method based on flux linkage characteristic coordinate transformation |
| CN109672386A (en) * | 2018-11-13 | 2019-04-23 | 江苏大学 | A kind of switch magnetoresistance motor rotor position detection method |
| CN111190128A (en) * | 2018-11-15 | 2020-05-22 | 北京自动化控制设备研究所 | Detection algorithm for BH characteristics of ferromagnetic material of reluctance motor |
| CN111190128B (en) * | 2018-11-15 | 2022-10-18 | 北京自动化控制设备研究所 | Detection algorithm for BH characteristics of ferromagnetic material of reluctance motor |
| CN110334386A (en) * | 2019-05-09 | 2019-10-15 | 深圳大学 | A kind of planar motor control method and terminal device based on parametric regression |
| CN112580209A (en) * | 2020-12-21 | 2021-03-30 | 湖南科技大学 | On-line torque estimation method of switched reluctance motor based on segmented analytical modeling |
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