CN108183639B - Least square classification speed regulation method for brushless direct current motor - Google Patents
Least square classification speed regulation method for brushless direct current motor Download PDFInfo
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- CN108183639B CN108183639B CN201810035364.1A CN201810035364A CN108183639B CN 108183639 B CN108183639 B CN 108183639B CN 201810035364 A CN201810035364 A CN 201810035364A CN 108183639 B CN108183639 B CN 108183639B
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- electromotive force
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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
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/08—Arrangements for controlling the speed or torque of a single motor
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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
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/14—Electronic commutators
- H02P6/16—Circuit arrangements for detecting position
- H02P6/18—Circuit arrangements for detecting position without separate position detecting elements
- H02P6/182—Circuit arrangements for detecting position without separate position detecting elements using back-emf in windings
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- Control Of Motors That Do Not Use Commutators (AREA)
Abstract
The invention discloses a least square classification speed regulation method for a brushless direct current motor, which comprises the following steps: 1) detecting the position of a motor rotor and regulating the speed by using the same motor provided with a position sensor, and detecting a back electromotive force signal; 2) taking the back electromotive force signal as input and the zero crossing point signal as output, and performing off-line training of a least square classifier; 3) and classifying the back electromotive force data of the brushless direct current motor control system by using a trained least square classifier to obtain a zero crossing point moment, so that the rotating speed and a phase change signal of the motor are calculated to realize phase change, the rotating speed of the motor is fed back to a PID (proportion integration differentiation) controller of the brushless direct current motor control system to calculate a control quantity, and the speed regulation is realized. The invention realizes the control of the brushless direct current motor without a position sensor, classifies the back electromotive force by using the least square classifier, is used for estimating the zero crossing point signal, and more accurately detects the unconventional back electromotive force zero crossing point.
Description
Technical Field
The invention relates to the technical field of brushless direct current motor control, in particular to a least square classification speed regulation method for a brushless direct current motor.
Background
If the brushless direct current motor determines the phase change time by using the back electromotive force zero crossing point, a Hall sensor is not needed to be installed to detect the position of a rotor, the back electromotive force is usually calculated by detecting the voltage of a non-conducting phase end, and then a phase change signal is obtained by detecting the back electromotive force zero point.
A back electromotive force zero classifier is designed to classify all detected back electromotive forces, non-zero points are classified into one class, and zero points are classified into the other class, so that zero-crossing points can be detected by the back electromotive force zero classifier. The least square classifier can ensure higher accuracy and reduce the calculated amount to the maximum extent, and can be applied to an embedded system such as a DSP. So far, the brushless direct current motor speed regulation without a position sensor by adopting a least square back electromotive force classifier has not appeared.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a least square classification speed regulation method for a brushless direct current motor, which aims to solve the problem of inaccurate detection of back electromotive force zero crossing points in the existing control method.
In order to achieve the purpose, the technical scheme of the invention is as follows: a least square classification speed regulation method for a brushless direct current motor comprises the following steps:
step S1: collecting off-line training data, detecting the position of a motor rotor and regulating the speed by using the same motor provided with a position sensor, and detecting a back electromotive force signal;
step S2: taking the back electromotive force signal as input and the zero crossing point signal as output, and performing off-line training of a least square classifier;
step S3: the sampling circuit is used for sampling the back electromotive force data of the brushless direct current motor control system without the position sensor, the trained least square classifier is used for classifying the on-line back electromotive force data to obtain the zero crossing point moment, so that the rotating speed and the phase change signal of the motor are calculated to realize phase change, the rotating speed of the motor is fed back to the PID controller of the brushless direct current motor control system to calculate the control quantity, and the speed regulation is realized.
Further, the step S2 is specifically:
training a least square classifier off line, keeping p-beat back electromotive force signals { e (k-1), …, e (k-p) } displayed on a time axis, marking a zero crossing point in each period, wherein the output of a zero crossing point sample is y (k) =1, and the output of a non-zero crossing point sample is y (k) = 0; taking p beats of counter electromotive force input signals { e (k), …, e (k-p +1) } and p beats of output signals { y (k), …, y (k-p +1) } as training samples, and solving an eigenvector x (k) as follows: x (k) = P (y (k-1),. eta, y (k-n), e (k),. eta, e (k-n)), where e (k), …, e (k-n) and y (k), …, y (k-n) are input and output at the k-th time of the classifier, respectively, and n represents the number of beats of input and output; and constructing a least square classifier based on a least square method.
Further, the specific method for obtaining the zero-crossing time in step S3 includes:
starting the motor by adopting a three-section starting method, wherein the three stages of rotor pre-positioning, frequency-boosting and voltage-boosting synchronous operation and switching self-synchronous operation are adopted, and stable back electromotive force is continuously detected after the starting is finished;
in a brushless DC motor drive system, a trained least squares classifier is used to detect zero crossings, assuming inputs { e (k), …, e (k-n +1) }, the decision function using the least squares classifier is expressed as: g (x) = ω · x (k); if g (x) > =0, y (k) = 1; if g (x) <0, y (k) = 0; x (k) is a feature vector: x (k) = P (y (k-1),. once, y (k-n), e (k),. once, e (k-n)), where e (k), …, e (k-n) and y (k), (k)), …, y (k-n) are input and output of the classifier at the k-th time, ω is the weight of the least squares classifier, e (k) is the back electromotive force, and y (k) is the classifier output, i.e., the zero-crossing signal;
and continuously acquiring back electromotive force data at the speed regulation stage of the brushless direct current motor, and inputting the back electromotive force data into a least square classifier to obtain the zero crossing point moment.
Compared with the prior art, the invention has the beneficial effects that: the invention saves position sensors, only 3 counter electromotive force sampling circuits need to be expanded on the inverter circuit, the hardware cost is low, the signal detection is not influenced by the environmental factors of temperature and dust, and the reliability is high;
the invention classifies the back electromotive force by utilizing the least square classifier for estimating the zero crossing point signal, has higher accuracy, has small calculated amount of the back electromotive force classifier obtained by off-line training, occupies a small part of CPU resource, is applied to the current mainstream DSP controlled brushless direct current motor control system, and can improve the control precision.
Drawings
FIG. 1 is a schematic flow chart of the least square classification speed control method of the brushless DC motor according to the present invention;
FIG. 2 is a schematic diagram of back EMF zero crossing detection according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a back emf data classification process according to an embodiment of the invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
For a trapezoidal wave brushless direct current motor with the counter electromotive force waveform of 120 degrees and the flat top width, six zero-crossing points are generated by three-phase counter electromotive force in one electric cycle, the delay of 30 degrees of electric angle displacement time is 6 phase change moments, and the accurate phase change moments influence the driving effect of the brushless direct current motor. The invention adopts a least square classification method to measure the rotating speed, only the back electromotive force of the power circuit is needed to be used as an input signal to calculate the rotating speed and the phase commutation moment, the phase commutation can be completed by replacing a rotor position signal measured by a mechanical sensor, and the rotating speed is fed back to the input end of a PID controller to realize speed regulation. The method comprises the steps of extracting a back electromotive force signal as a sample from a brushless direct current motor control system with a position sensor to train a least square classifier, wherein the trained least square classifier can realize back electromotive force zero crossing point classification, due to learning capacity of the least square classifier, unconventional back electromotive force zero crossing point detection is more accurate, Boolean value is output, the rotating speed and phase change time of a motor are calculated through the output, and accurate speed regulation is realized through a PID algorithm.
As shown in fig. 1, a least square classification speed regulation method for a brushless dc motor of the present invention includes:
step S1: collecting off-line training data, detecting the position of a motor rotor and regulating the speed by using the same motor provided with a position sensor, and detecting a back electromotive force signal;
step S2: taking the back electromotive force signal as input and the zero crossing point signal as output, and performing off-line training of a least square classifier;
step S3: the sampling circuit is used for sampling the back electromotive force data of the brushless direct current motor control system without the position sensor, the trained least square classifier is used for classifying the on-line back electromotive force data to obtain the zero crossing point moment, so that the rotating speed and the phase change signal of the motor are calculated to realize phase change, the rotating speed of the motor is fed back to the PID controller of the brushless direct current motor control system to calculate the control quantity, and the speed regulation is realized.
The step S2 specifically includes:
training a least square classifier off line, keeping p-beat back electromotive force signals { e (k-1), …, e (k-p) } displayed on a time axis, marking a zero crossing point in each period, wherein the output of a zero crossing point sample is y (k) =1, and the output of a non-zero crossing point sample is y (k) = 0; taking p beats of counter electromotive force input signals { e (k), …, e (k-p +1) } and p beats of output signals { y (k), …, y (k-p +1) } as training samples, and solving an eigenvector x (k) as follows: x (k) = P (y (k-1),. eta, y (k-n), e (k),. eta, e (k-n)), where e (k), …, e (k-n) and y (k), …, y (k-n) are input and output at the k-th time of the classifier, respectively, and n represents the number of beats of input and output; and constructing a least square classifier based on a least square method.
The specific method for obtaining the zero-crossing point time in step S3 includes:
starting the motor by adopting a three-section starting method, wherein the three stages of rotor pre-positioning, frequency-boosting and voltage-boosting synchronous operation and switching self-synchronous operation are adopted, and stable back electromotive force is continuously detected after the starting is finished;
in a brushless DC motor drive system, a trained least squares classifier is used to detect zero crossings, assuming inputs { e (k), …, e (k-n +1) }, the decision function using the least squares classifier is expressed as: g (x) = ω · x (k); if g (x) > =0, y (k) = 1; if g (x) <0, y (k) = 0; x (k) is a feature vector: x (k) = P (y (k-1),. once, y (k-n), e (k),. once, e (k-n)), where e (k), …, e (k-n) and y (k), (k)), …, y (k-n) are input and output of the classifier at the k-th time, ω is the weight of the least squares classifier, e (k) is the back electromotive force, and y (k) is the classifier output, i.e., the zero-crossing signal;
and continuously acquiring back electromotive force data at the speed regulation stage of the brushless direct current motor, and inputting the back electromotive force data into a least square classifier to obtain the zero crossing point moment.
As shown in fig. 2, for a trapezoidal wave brushless dc motor with a 120 ° flat-top width back emf waveform, six zero-crossing points are generated by three-phase back emf in one electrical cycle, respectively Z1-Z6, and six phase-change points are at times S1-S6, respectively VT1-VT 6. The driving circuit adopts a two-to-two conduction mode, VT5VT6 is in a conduction state at the beginning, after a zero crossing point time Z1 is detected, an electrical angle is delayed by 30 degrees, the phase change time S1 can be obtained, VT1VT6 is controlled to be conducted, then Z2 is detected, and zero crossing point detection and phase change are carried out in sequence and alternately according to the position shown in the figure, so that the motor can be driven to rotate.
As shown in fig. 3, the a/D conversion result is read to obtain the back emf data, which back emf needs to be read is determined according to different switch conducting states, the value is normalized to obtain the feature vector, the back emf zero-crossing point is determined by using the least square classifier, the output of the back emf zero-crossing point is set as y (k) =1, if the zero-crossing point is detected, the phase change is completed according to the back emf, and finally the rotation speed is adjusted.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and achievements of the present invention, and it should be understood that the above-mentioned embodiments are only examples of the present invention, and should not be construed as limiting the present invention, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A least square classification speed regulation method for a brushless direct current motor is characterized by comprising the following steps:
step S1: collecting off-line training data, detecting the position of a motor rotor and regulating the speed by using the same motor provided with a position sensor, and detecting a back electromotive force signal;
step S2: taking the back electromotive force signal as input and the zero crossing point signal as output, and performing off-line training of a least square classifier;
step S3: sampling back electromotive force data of a brushless direct current motor control system without a position sensor by using a sampling circuit, classifying the on-line back electromotive force data by using a trained least square classifier to obtain zero crossing point time, calculating the rotating speed of the motor and a commutation signal, realizing commutation, feeding the rotating speed of the motor back into a PID (proportion integration differentiation) controller of the brushless direct current motor control system to calculate control quantity, and realizing speed regulation;
the step S2 specifically includes:
training a least square classifier off line, keeping p-beat back electromotive force signals { e (k-1), …, e (k-p) } displayed on a time axis, marking a zero crossing point in each period, wherein the output of a zero crossing point sample is y (k) =1, and the output of a non-zero crossing point sample is y (k) = 0; taking p beats of counter electromotive force input signals { e (k), …, e (k-p +1) } and p beats of output signals { y (k), …, y (k-p +1) } as training samples, and solving an eigenvector x (k) as follows: x (k) = P (y (k-1),. eta, y (k-n), e (k),. eta, e (k-n)), where e (k), …, e (k-n) and y (k), …, y (k-n) are input and output at the k-th time of the classifier, respectively, and n represents the number of beats of input and output; constructing a least square classifier based on a least square method;
the specific method for obtaining the zero-crossing point time in step S3 includes:
starting the motor by adopting a three-section starting method, wherein the three stages of rotor pre-positioning, frequency-boosting and voltage-boosting synchronous operation and switching self-synchronous operation are adopted, and stable back electromotive force is continuously detected after the starting is finished;
in a brushless DC motor drive system, a trained least squares classifier is used to detect zero crossings, assuming inputs { e (k), …, e (k-n +1) }, the decision function using the least squares classifier is expressed as: g (x) = ω · x (k); if g (x) > =0, y (k) = 1; if g (x) <0, y (k) = 0; omega is the weight of the least square classifier, e (k) is the back electromotive force, y (k) is the classifier output, namely the zero crossing point signal;
and continuously acquiring back electromotive force data at the speed regulation stage of the brushless direct current motor, and inputting the back electromotive force data into a least square classifier to obtain the zero crossing point moment.
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| CN113572395A (en) * | 2020-04-26 | 2021-10-29 | 北京信息科技大学 | Adaptive real-time correction method for commutation error of brushless motor without position sensor |
| CN112104272A (en) * | 2020-09-14 | 2020-12-18 | 中船重工(重庆)西南装备研究院有限公司 | Position detection method for brushless direct current motor without position sensor |
| CN112505576A (en) * | 2020-12-04 | 2021-03-16 | 厦门市爱维达电子有限公司 | Power failure rapid detection method based on least square classifier |
| CN113258835B (en) * | 2021-04-20 | 2022-09-09 | 山东大学 | Direct-current brushless motor control method and system for vehicle engine cooling fan |
| CN113411013B (en) * | 2021-07-14 | 2022-06-10 | 北京航空航天大学 | Brushless direct current motor control system and method for back electromotive force function integral prediction |
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| CN103560725B (en) * | 2013-11-15 | 2016-08-17 | 东南大学 | A kind of Brushless DC Motor Position detection method independent of rotating speed |
| CN106953561B (en) * | 2017-04-24 | 2019-06-07 | 福州大学 | A kind of brushed DC motor speed regulating method to be tested the speed based on least squared classified |
| CN107482962A (en) * | 2017-09-11 | 2017-12-15 | 西北工业大学 | The commutation position detection phase change method of brushless direct current motor sensorless |
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