CN107634685A - A kind of method for suppressing torque ripple based on adaptive noise cancel- ation - Google Patents
A kind of method for suppressing torque ripple based on adaptive noise cancel- ation Download PDFInfo
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- CN107634685A CN107634685A CN201711072960.9A CN201711072960A CN107634685A CN 107634685 A CN107634685 A CN 107634685A CN 201711072960 A CN201711072960 A CN 201711072960A CN 107634685 A CN107634685 A CN 107634685A
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Abstract
A kind of method for suppressing torque ripple based on adaptive noise cancel- ation, mainly it is achieved by MCU, power driver module, current detection module, adaptive noise cancel- ation module, MCU, power driver module, current detection module are sequentially connected, current detection module is connected with brshless DC motor, and brshless DC motor is connected to MCU by adaptive noise cancel- ation module；MCU module is changed, rotating speed calculating, and by specific control strategy formation electric current and rotating speed double circle structure, form complete two close cycles servo-drive system by receiving the rotor-position feedback signal and current feedback signal that HALL sensors gather by A/D.Adaptive noise cancel- ation method is introduced into the speed and current double closed loop governing system of permanent-magnet brushless DC electric machine by the design, for eliminating the noise being superimposed in HALL signals, avoid noise from entering in motor servo system, torque pulsation caused by noise is mixed into so as to reduce HALL signals.
Description
Technical Field
The invention relates to the field of motors, in particular to a torque ripple suppression method based on adaptive noise elimination.
Background
The permanent magnet brushless motor can be regarded as a direct current motor which replaces mechanical commutation with an electronic commutation device, and mainly comprises a permanent magnet motor body, a rotor position sensor and an electronic commutation circuit. The permanent magnet dc brushless motor has many similarities with the conventional dc motor, no matter the structure or control mode: the rotor with permanent magnet is used to replace the stator magnetic pole of the brush DC motor; replacing the armature with a stator having a multi-phase winding; the mechanical commutator and brushes are replaced by an electronic commutator consisting of a solid state inverter and a shaft position detector.
In the inductive permanent magnet brushless dc motor, a HALL sensor is indispensable as a device for detecting the position of the rotor. The position of the rotor is detected by sensing the change of a magnetic field in the rotating process of the rotor of the brushless direct current motor, and a detection signal is fed back to a control chip to form a rotating speed outer ring of a double-closed-loop control system of the brushless direct current motor. The HALL sensor, as a sensitive device, has different degrees of sensitivity to light, heat and mechanical stress besides magnetic sensitivity, and when the brushless dc motor works in complex environments such as dusty, high and low temperature, noise is easily superposed on HALL feedback signals to enter a servo system, which affects the processing of real HALL signals and increases the torque ripple of the brushless dc motor. The adaptive noise elimination method can track input statistics under the condition that a small amount of noise priori knowledge is unknown or known in a complex environment, and the tap weight coefficient is continuously adjusted to adapt to the statistical characteristics of the HALL signal and the noise, so that noise interference is eliminated, and torque ripple caused by the superposition of the HALL signal and the noise is reduced.
Disclosure of Invention
The present invention aims to overcome the defects of the prior art and provide a technical solution to the above problems.
A torque ripple suppression method based on adaptive noise elimination is mainly realized through an MCU, a power driving module, a current detection module and an adaptive noise elimination module, wherein the MCU, the power driving module and the current detection module are sequentially connected, the current detection module is connected with a brushless direct current motor, and the brushless direct current motor is connected to the MCU through the adaptive noise elimination module; the MCU module forms a current and rotating speed double closed loop structure through receiving a rotor position feedback signal and a current feedback signal acquired by the HALL sensor, performing A/D conversion and rotating speed calculation, and forming a complete double closed loop servo system through a specific control strategy; the power driving module comprises a three-phase bridge type inverter circuit and a current detection circuit; the PWM signal output by the MCU controls the on-off of a switch in the inverter to drive the permanent magnet brushless direct current motor, so that the phase change function of the permanent magnet brushless direct current motor is realized.
Preferably, the adaptive noise cancellation module delays the HALL signal d (n) superimposed with the noise by using the temporal irrelevance of the white noise, and inputs the delayed HALL signal d (n) into the adaptive filter, where the useful signal in d (n) has a strong correlation with the useful signal in the delayed signal d' (n), and the noise is uncorrelated in time, so that the adaptive filter can predict the useful signal.
Preferably, the core of the adaptive noise elimination module is an adaptive filter, and the adaptive algorithm realizes optimal filtering by controlling parameters of the adaptive filter; the system employs an RLS filtering algorithm.
Preferably, the RLS filtering algorithm:
y(n)＝w(n-1)u(n)；
e(n)＝d(n)-y(n)；
w(n)＝w(n-1)+k H (n)e(n)；
P(n)＝λ -1 P(n-1)-λ -1 k(n)u H (n)P(n-1)；
wherein, the initial value w (0) =0 of the tap weight vector, the initial value P (0) = δ of the inverse correlation matrix -1 I, delta is a regularization parameter, and I is an identity matrix; λ is forgetting factor, 0<λ< 1, k (n) is the gain vector and e (n) is the prior estimation error.
Compared with the prior art, the invention has the beneficial effects that:
1. the rotating speed single closed loop speed regulating system is difficult to meet the control requirement under the conditions of complex controlled objects and a plurality of interference factors, and the rotating speed-current double closed loop control system has good speed regulating performance and anti-interference performance, better solves the defects in the single closed loop system, has good starting, running and control performance, and is a direct current speed regulating system with best performance and most extensive application.
2. The design introduces the self-adaptive noise elimination method into a rotating speed-current double closed-loop speed regulating system of the permanent magnet brushless direct current motor, and is used for eliminating the noise superposed in the HALL signal and preventing the noise from entering a motor servo system, thereby reducing the torque pulsation caused by the noise mixed in the HALL signal.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a system diagram of a method for adaptive noise cancellation based torque ripple suppression;
FIG. 2 is a block diagram of an ANC system in an adaptive noise cancellation based torque ripple suppression method;
FIG. 3 is a torque comparison and a partial enlarged view thereof for an adaptive noise cancellation based torque ripple suppression method;
fig. 4-5 are a comparison of rotational speeds and a close-up view thereof for an adaptive noise cancellation based torque ripple suppression method.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, in an embodiment of the present invention, a method for suppressing torque ripple based on adaptive noise cancellation is mainly implemented by an MCU, a power driving module, a current detecting module, and an Adaptive Noise Cancellation (ANC) module, where the MCU, the power driving module, and the current detecting module are connected in sequence, the current detecting module is connected to a brushless dc motor (BLDCM), and the brushless dc motor (BLDCM) is connected to the MCU through the Adaptive Noise Cancellation (ANC) module; the MCU module forms a current and rotating speed double closed loop structure through receiving a rotor position feedback signal and a current feedback signal acquired by the HALL sensor, performing A/D conversion and rotating speed calculation and a specific control strategy to form a complete double closed loop servo system; the power driving module comprises a three-phase bridge type inverter circuit and a current detection circuit. The PWM signal output by the MCU controls the on-off of a switch in the inverter to drive the permanent magnet brushless direct current motor, so that the phase change function of the permanent magnet brushless direct current motor is realized. The rotating speed single closed loop speed regulating system is difficult to meet the control requirement under the conditions of complex controlled objects and a plurality of interference factors, and the rotating speed-current double closed loop control system has good speed regulating performance and anti-interference performance, better solves the defects in the single closed loop system, has good starting, running and control performance, and is a direct current speed regulating system with best performance and most extensive application. The design introduces a self-adaptive noise elimination method into a rotating speed-current double closed-loop speed regulating system of the permanent magnet brushless direct current motor, and is used for eliminating the noise superposed in the HALL signal and preventing the noise from entering a motor servo system, thereby reducing the torque pulsation caused by the noise mixed in the HALL signal.
As shown in fig. 2, the ANC system uses the temporal irrelevance of white noise to delay the HALL signal d (n) with the noise superimposed thereon and input the delayed HALL signal d (n) into the adaptive filter, where the useful signal in d (n) has strong correlation with the useful signal in the delayed signal d' (n), and the noise is uncorrelated in time, so that the adaptive filter can predict the useful signal. Thereby achieving the purpose of noise elimination.
The core of the ANC system is an adaptive filter, and the adaptive algorithm realizes optimal filtering by controlling the parameters of the adaptive filter. Compared with the Least Mean square algorithm (LMS, least Mean square), the Recursive Least square algorithm (RLS) has faster convergence speed and stronger capacity of resisting the outburst value interference. The system employs an RLS filtering algorithm.
RLS algorithm:
y(n)＝w(n-1)u(n)
e(n)＝d(n)-y(n)
w(n)＝w(n-1)+k H (n)e(n)
P(n)＝λ -1 P(n-1)-λ -1 k(n)u H (n)P(n-1)
wherein, the initial value w (0) =0 of the tap weight vector, the initial value P (0) = δ of the inverse correlation matrix -1 I, δ is the regularization parameter, I is the identity matrix. λ is forgetting factor, 0<λ< 1, k (n) is the gain vector and e (n) is the prior estimation error.
The comparison of the torque ripple of the permanent magnet brushless direct current motor speed regulating system with or without the ANC system is shown in FIG. 3, wherein blue is the torque condition without the ANC system, and orange is the torque ripple condition with the ANC system. The motor torque of the speed regulating system without the ANC system has larger vibration at the balance position, and the vibration of the speed regulating system with the ANC system is obviously reduced. And the torque overshoot is reduced from 87.3% to 19.6%.
As shown in fig. 4-5, it can be seen from the enlarged partial views of the rotating speed that the ANC system is added to the motor speed regulating system to reduce the overshoot of the rotating speed.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (5)
1. A torque ripple suppression method based on adaptive noise elimination is mainly realized through an MCU, a power driving module, a current detection module and an adaptive noise elimination module, and is characterized in that the MCU, the power driving module and the current detection module are sequentially connected, the current detection module is connected with a brushless direct current motor, and the brushless direct current motor is connected to the MCU through the adaptive noise elimination module; the MCU module forms a current and rotating speed double closed loop structure through receiving a rotor position feedback signal and a current feedback signal acquired by the HALL sensor, performing A/D conversion and rotating speed calculation, and forming a complete double closed loop servo system through a specific control strategy; the PWM signal output by the MCU controls the on-off of a switch in the inverter to drive the permanent magnet brushless direct current motor, thereby realizing the phase change function.
2. The method as claimed in claim 1, wherein the adaptive noise cancellation module delays the HALL signal d (n) of the superimposed noise by using the temporal irrelevancy of white noise and inputs the delayed HALL signal into the adaptive filter, the useful signal in d (n) has strong correlation with the useful signal in the delayed signal d' (n), and the noise is uncorrelated in time, so that the adaptive filter can predict the useful signal.
3. The adaptive noise cancellation-based torque ripple suppression method according to claim 1, wherein the core of the adaptive noise cancellation module is an adaptive filter, and an adaptive algorithm implements optimal filtering by controlling parameters of the adaptive filter; the system employs an RLS filtering algorithm.
4. The adaptive noise cancellation-based torque ripple suppression method according to claim 3, wherein the RLS filtering algorithm:
y(n)＝w(n-1)u(n)；
e(n)＝d(n)-y(n)；
w(n)＝w(n-1)+k H (n)e(n)；
P(n)＝λ -1 P(n-1)-λ -1 k(n)u H (n)P(n-1)；
wherein, the initial value w (0) =0 of the tap weight vector, the initial value P (0) = δ of the inverse correlation matrix -1 I, delta is a regularization parameter, and I is an identity matrix; λ is forgetting factor, 0<λ&And lt, 1, k (n) is a gain vector, and e (n) is an a priori estimation error.
5. The adaptive noise cancellation-based torque ripple suppression method according to claim 1, wherein the power driving module comprises a three-phase bridge inverter circuit and a current detection circuit.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110912536A (en) * | 2019-12-24 | 2020-03-24 | 昆山九毫米电子科技有限公司 | RLS adaptive filtering method for open type shock wave target-scoring system |
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| CN101320996A (en) * | 2008-05-27 | 2008-12-10 | 中山大学 | Self-adapting noise elimination apparatus and method |
| CN104092417A (en) * | 2014-06-30 | 2014-10-08 | 英特格灵芯片(天津)有限公司 | Self-adaptive processing method and device for motor rotor position signals and control system |
| US20170088126A1 (en) * | 2015-09-03 | 2017-03-30 | Ferrari S.P.A. | Method to control an electric motor with adjustment of the value of the equivalent impedance |
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2017
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| CN101320996A (en) * | 2008-05-27 | 2008-12-10 | 中山大学 | Self-adapting noise elimination apparatus and method |
| CN104092417A (en) * | 2014-06-30 | 2014-10-08 | 英特格灵芯片(天津)有限公司 | Self-adaptive processing method and device for motor rotor position signals and control system |
| US20170088126A1 (en) * | 2015-09-03 | 2017-03-30 | Ferrari S.P.A. | Method to control an electric motor with adjustment of the value of the equivalent impedance |
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| GAOLIN WANG等: "Position Estimation Error Reduction Using Recursive-Least-Square Adaptive Filter for Model-Based Sensorless Interior Permanent-Magnet Synchronous Motor Drives", 《IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》 * |
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| CN110912536A (en) * | 2019-12-24 | 2020-03-24 | 昆山九毫米电子科技有限公司 | RLS adaptive filtering method for open type shock wave target-scoring system |
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Inventor after: He Jiai Inventor after: He Guotao Inventor after: Zhang Fan Inventor after: Yu Qi Inventor after: Ma Yun Inventor before: He Guotao Inventor before: Zhang Fan Inventor before: Yu Qi Inventor before: Ma Yun |
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Effective date of registration: 20181023 Address after: 528434 villager Road 8, Zhongshan, Guangdong Applicant after: Zhongshan Puyang Electronic Technology Co., Ltd. Applicant after: Lanzhou University Of Technology Address before: 528434 Fusha Town Industrial Park, Zhongshan, Guangdong (Donlim power side) Applicant before: Zhongshan Puyang Electronic Technology Co., Ltd. |
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