The present invention relates to a technique for improving versatility of a motor control system. Here, the motor control system is a system for controlling the motor in accordance with the specification of a target to be driven by the motor.
Motors and motor control systems for controlling the motors are widely applied as means to convert electric power into mechanical output, to fans, pumps, compressors, automobiles, railroads, for example. On the other hand, as a problem of the motor control system, a step-out caused by a sudden load torque (instability of motor speed and torque), vibration caused by pulsation load torque, and the like are known. As techniques for detecting and preventing these problems, there are PTLs 1 and 2.
In PTL 1, in order to detect the step-out caused by the sudden load, a motor current is Fourier-analyzed and its pulsating component is compared with a reference value. If a step-out occurs due to the sudden load torque, since the pulsating component of the motor current exceeds the reference value, it is possible to detect the step-out. Furthermore, by transmitting information on the loss of synchronization detection to a host controller, safety can be improved.
PTL 2 reduces vibrations due to the pulsation load torques. A rotor position is estimated from the motor current, and the pulsation load torque is estimated by substituting the position estimation value into the motion equation. Next, Fourier analysis is performed on the pulsation load torque, and the output voltage of the inverter is pulsed so as to cancel each frequency component. If the pulsation amount of the output voltage is appropriate, the motor torque and the pulsation load torque cancel each other out and the vibration is reduced.
PTL 1: JP-A-2012-50155
PTL 2: Japanese Patent No. 4221307
A common problem of PTLs 1 and 2 is the necessity of an adjustment work of the control parameters. For example, there are a reference value of a current pulsation component of PTL 1, an upper limit order of the Fourier analysis of PTL 2, and the like. When the reference value of the current pulsation component is set to a lower value, erroneous detection increases, and when the reference value is set to a high value, oversight is not overlooked. Also, when the upper limit number of Fourier analysis is set to a low value, the vibration cannot be suppressed, and when the upper limit is set to a high value, the calculation amount increases unnecessarily. Therefore, these control parameters need to be adjusted for each motor control system, and the development period is prolonged.
An object of the present invention is to omit the adjustment work of the motor control system and to increase versatility.
Features of the present invention for solving the above problem is as follows, for example.
Provided is a motor control system including: an inverter which outputs a voltage to a motor based on a voltage command; a current detecting unit which outputs a current detection value based on a current flowing through a motor of a state quantity detecting unit 42; a voltage command calculating unit which outputs the voltage command of the state quantity detecting unit 42 based on a high-order command and the current detection value of the state quantity detecting unit 42; a storage unit which outputs a data set of the quantity of state of the state quantity detecting unit 42 based on the quantity of state of a driving target of the motor of the state quantity detecting unit 42; an abnormality degree calculation equation updating unit which outputs an abnormality degree calculation equation for computing the abnormality degree of the driving target of the state quantity detecting unit 42 based on the data set of the state quantity detecting unit 42; an abnormality degree calculating unit which outputs the abnormality degree based on the quantity of state of the state quantity detecting unit 42 and the abnormality degree calculation equation of the state quantity detecting unit 42; and a voltage adjusting unit which outputs an adjustment voltage for adjusting the voltage command of the state quantity detecting unit 42 based on the abnormality degree of the state quantity detecting unit 42.
According to the present invention, the adjustment work of the motor control system can be omitted, and versatility can be enhanced. The problems, configurations and effects other than those described above will be clarified by the description of the embodiments below.
Hereinafter, embodiments of the present invention will be described with reference to the drawings and the like. The following description illustrates concrete examples of the contents of the present invention, the present invention is not limited to these descriptions, and various changes and modifications made by those skilled in the art can be made within the scope of the technical idea disclosed in this specification. Further, in all the drawings for explaining the present invention, those having the same function will be denoted by the same reference numerals, and the repetitive description thereof may be omitted.
A first embodiment will be described with reference to
When three-phase AC voltages (a U-phase voltage Vu, a V-phase voltage Vv, and a W-phase voltage Vw) are applied to a motor 1 by an inverter 2, three-phase AC currents (a U-phase current Iu, a V-phase current Iv, and a W-phase current Iw) flow, and a motor torque τ is generated.
A quantity of state of the motor 1 will be described.
[Equation 1]
τ=3/2Pm(Kc+(Ld−Lq)Id)Iq (Equation 1)
The above is a description of the quantity of state of the motor 1.
The inverter 2 of
The current detecting unit 3 outputs the detected value of the three-phase alternating current of the motor 1. In other words, the current detecting unit 3 outputs the current detection value, based on the current flowing through the motor 1. In order to simplify the description, it is assumed that the detection error is negligible, and the three-phase alternating current and its detection value are both denoted by symbols Iu, Iv, and Iw.
The driving target 4 is a system in which the motor 1 is used as a drive source. In
The voltage command calculating unit 5 outputs the voltage command V* based on the high-order command and the current detection value. The high-order command is a command given from a host control system to the motor control system, and is, for example, a speed command f* or a torque command τ*. Specifically, the voltage command calculating unit 5 is, for example, vector control or V/f control.
A storage unit 6 stores the quantity of state p and outputs the data set P thereof. A difference between the quantity of state p and the data set P is that the quantity of state p is an instantaneous value and does not have a history, whereas the data set P has a history.
An abnormality degree calculation equation updating unit 7 outputs an abnormality degree calculation equation f(p) based on the data set P. The abnormality degree calculation equation f(p) is an equation for calculating the abnormality degree An, and the abnormality degree An is an index which represents the degree of the quantity of state p deviates from the normal state of the driving target 4. The normal state is a state in which the driving target 4 is in the most desirable state, for example, an operating state in which the driving target 4 can be driven with high efficiency and low vibration. When the quantity of state p is in the normal state, the abnormality degree An is zero, and as the quantity of state p deviates from the ideal state, the abnormality degree An increases.
For example, when the driving target 4 is a compressor, the compressor pressure is considered as the quantity of state p, and it is assumed that the normal state is a point A in
The abnormality degree calculating unit 8 outputs the abnormality degree “An=f(p)” based on the quantity of state p and the abnormality degree calculating formula f(p). In
The voltage adjusting unit 9 outputs an adjustment voltage ΔV for adjusting the voltage command based on the abnormality degree An. The conversion from the abnormality degree An to the adjustment voltage ΔV is, for example, as illustrated in
The constituent elements in the first embodiment are as described above. Characteristic units of the present invention will be described.
The characteristic unit of the present invention is feedback provided by the storage unit 6, the abnormality degree calculation equation updating unit 7, the abnormality degree calculating unit 8, and the voltage adjusting unit 9. When the driving target 4 is normal, the normal state illustrated in
(1) Voltage command calculating unit 5 is feedback of the current detection value, that is, feedback of information on the motor 1
(2) On the other hand, the voltage adjusting unit 9 is feedback concerning the information of the driving target 4.
In order to detect the manufacturing error of the driving target 4 or the characteristic change during operation, feedback of the voltage adjusting unit 9 of (2) is indispensable. Conversely, by providing this, it is possible to omit the adjustment work of the motor control system and to enhance versatility.
The above description is about the characteristic units of the present invention. Next, the effects of the present invention will be described through specific examples at the time of starting the motor and at the time of pulsation load.
This is achieved, for example, as illustrated in
In
(1) The threshold value px varies depending on manufacturing errors of the motor 1 and the driving target 4 or characteristic changes during operation.
(2) Since there are a plurality of quantities of state p, there are also plural threshold values px.
(3) There is a case where abnormality of the driving target 4 cannot be determined only by the magnitude relation of the threshold value px. For example, there is a case of determining an abnormality by the distortion rate or frequency characteristic of the quantity of state p.
According to the configuration of the present invention, the problems of (1) to (3) above can be avoided, and re-startup of the motor 1 can be automated.
(1) Amplitude: the value obtained by converting the torque pulsation amplitude into the voltage amplitude, using the electrical characteristic of the motor 1
(2) Frequency: same as the torque pulsation frequency (driving frequency of the compressor)
This can be achieved, for example, by using a vector control including the torque pulsation suppression control as the voltage command calculating unit 5. As a result, the quantity of state p at times t1 to t2 is reduced as compared with time 0 to t1. However, since the pulsation of the load torque includes harmonic components, the quantity of state p does not become zero. Therefore, at the times t2 to t3, the voltage adjusting unit 9 outputs the adjustment voltage ΔV including the harmonic to reduce the quantity of state p. Even after the time t3, the adjustment voltage ΔV is optimized by feedback of the state quantity detecting unit 42, the storage unit 6, the abnormality degree calculation equation updating unit 7, the abnormality degree calculating unit 8, and the voltage adjusting unit 9, and the quantity of state p is reduced. At the time t4, the quantity of state p becomes zero, and the optimization of the adjustment voltage ΔV is completed. The adjustment voltage ΔV after optimization has the following characteristics.
(1) Amplitude: it is a harmonic, and becomes variable within the cycle T of the compressor.
(2) Frequency: same as the torque pulsation frequency (driving frequency of the compressor)
The difference between the voltage command V* and the adjustment voltage Δ is the amplitude of (1), the former being a sine wave and the latter being a harmonic. Since the final voltage command V** is generated by these sums, arbitrary torque pulsation can be canceled and the quantity of state p can be reduced.
In
(1) The responsiveness of the required voltage command calculating unit 5 depends on the mechanical characteristics of the compressor.
(2) An improvement in responsiveness of the voltage command calculating unit 5 makes the motor control system unstable.
According to the configuration of the present invention, the problems of (1) and (2) above can be avoided, and the vibration of the compressor can be automatically reduced.
The above is the effect of the present invention. Furthermore, by changing the following units, its effect can be enhanced.
The abnormality degree calculation equation updating unit 7 outputs two or more abnormality degree calculation equations f(p), the abnormality degree calculating unit 8 outputs two or more abnormality degrees An, and the voltage adjusting unit 9 may control the adjustment voltage ΔV such that at least one other among the plurality of abnormality degrees is a minimum value in a range in which at least one of the plurality of abnormality degrees is a predetermined value or less. Thus, in a case where there is a trade-off relation between the plurality of abnormality degrees, the relation can be optimized.
For example,
At the times 0 to t1 in
On the other hand, since the rotational speed w is pulsating, the abnormality degree An2 is positive. When the storage unit 6, the abnormality degree calculation equation updating unit 7, the abnormality degree calculating unit 8, and the voltage adjusting unit 9 are validated at the time t1, the adjustment voltage ΔV is generated. As a result, since the motor torque τ pulsates and the differential torque from the load torque τL becomes small, the pulsation of the rotational speed ωr and the abnormality degree An2 also decrease.
On the other hand, since the d-axis current Id and the q-axis current Iq of (Equation 1) pulsate, the d-axis current Id and the q-axis current Iq become larger than a case where they are controlled to be constant and minimum, and the copper loss and the abnormality degree An1 also increase. As described above, the abnormality degrees An1 and An2 are in a trade-off relationship, and as the abnormality degree An2 is reduced, the abnormality degree An1 increases. Then, at the time t2, the abnormality degree An1 becomes equal to the abnormality degree allowable maximum value, and here, the optimization of the adjustment voltage ΔV is completed.
As described above, according to the configuration of the present invention, a trade-off between abnormality degrees can be automatically optimized. The type of abnormality increases as the size of the driving target 4 increases, and the trade-off relation between them becomes complicated, but the present invention is particularly effective in such a case.
The motor control system may be provided with a coupling unit 11 between the motor 1 and the driving target 4, and may be provided with a learning mode in which the motor 1 and the driving target 4 are temporarily disconnected.
In the learning mode, the coupling unit 11 disconnects the motor 1 and the driving target 4 and connects the servo system instead. As a substitute for the driving target 4, the servo system simulates all or a part of considered driving patterns. At this time, the storage unit 6 outputs a plurality of data sets P, and the abnormality degree calculation equation updating unit 7 outputs the abnormality degree calculation equation f(p) at least once. After the output, the motor 1 and the servo system are disconnected from each other, and the driving target 4 is reconnected instead. After reconnection, an abnormality degree An is calculated based on the abnormality degree calculation equation f(p) which is output at the time of the learning mode. By using such a learning mode, the following effects can be obtained.
(1) When the driving target 4 is a large-scale system and cannot be moved with an arbitrary operation pattern, the data set P can be acquired in a short time.
(2) It is possible to acquire the data set P of a less frequent operation pattern in the driving target 4 in advance.
As a result of the above, it is possible to shorten the period until the abnormality degree calculation equation updating unit 7 initially outputs the abnormality degree calculation equation f(p), and it is also possible to shorten the introduction period of the motor control system.
Instead of the data set of the quantity of state p, the storage unit 6 may output the data set of the quantity of state p and the current detection value. For example, it is assumed that the driving target 4 is a fan, the quantity of state p is the torque of the fan rotation shaft, and the current detection value is the amplitude |Iu| of the U-phase current Iu. At this time, the normal state is the straight line L as illustrated in
The storage unit 6 may output only the data set of the current detection value. For example, the normal state of the U-phase current amplitude |Iu| and the V-phase current amplitude |Iv| has an equivalent relation as illustrated in
The abnormality degree calculating unit 8 can enhance the accuracy of the abnormality degree An by outputting the abnormality degree An based on the data set P instead of the quantity of state p. That is, by incorporating the temporal change amount of the quantity of state p in the abnormality degree calculation, it is possible to detect a sudden abnormality, for example, an instantaneous power failure.
It is desirable that the update cycle of the abnormality degree calculation equation f(p) provided by the abnormality degree calculation equation updating unit 7 is longer than the calculation cycle of the abnormality degree calculating unit 8. As a result, since the calculation load of the abnormality degree calculation equation updating unit 7 is reduced and the responsiveness of the adjustment voltage ΔV is not deteriorated, the omission effect of the adjustment operation is not deteriorated. This is because the abnormality detection speed of the driving target 4 depends on the calculation cycle of the abnormality degree calculating unit 8, but does not depend on the content of the abnormality degree calculation equation f(p). In other words, the content of the abnormality degree calculation equation f(p) affects the abnormality degree detection accuracy of the driving target 4, and the update thereof is unnecessary after the learning has been sufficiently completed. Therefore, it is desirable that the update cycle of the abnormality degree calculation equation f(p) provided by the abnormality degree calculation equation updating unit 7 is longer than the calculation cycle of the abnormality degree calculating unit 8.
The PI control unit 511 performs the PI control on the difference between the rotational speed command f* and the rotational speed ω to calculate the torque command τ*. The PI control unit 512 performs the PI control on the difference between the d-axis current command Id*, the q-axis current command Iq* and the d-axis current Id, the q-axis current Iq to calculate the d-axis current command Id** and the q-axis current command Iq**. The coordinate transforming unit 521 transforms the three-phase alternating currents Iu, Iv, and Iw into the d-axis current Id and the q-axis current Iq, using the rotor phase θd as illustrated in
According to the configuration of
(1) It is possible to separate the responsiveness of the voltage command calculating unit 5 and the voltage adjusting unit 9. That is, even if the voltage adjusting unit 9 is newly added to the existing voltage command calculating unit 5, the response of the voltage command V* and the adjustment voltage ΔV do not interfere with each other, and the instability of the motor control system can be prevented.
(2) Robust against high frequency noise of the quantity of state p included in the abnormality degree An is achieved.
In this way, since the voltage adjusting unit 9 includes the integrating unit, it is possible to improve the robustness, without changing the existing motor control system. Although the responsiveness of the adjustment voltage ΔV is lowered, the responsiveness of the motor control system can be secured by the voltage command calculating unit 5.
The cluster classifying unit 71 classifies the data set P into the respective clusters based on the cluster center of gravity X, and outputs the classification result Q thereof.
The cluster center-of-gravity position calculating unit 72 recalculates the position of the cluster center of gravity X and outputs it. For example, in
The position of the new center of gravity X is also output to the abnormality degree calculation equation calculating unit 73. The abnormality degree calculation equation calculating unit 73 outputs the abnormality degree calculation equation f(p) with respect to a certain quantity of state p by setting the distance from the center of gravity X which is the shortest distance as the abnormality degree An. That is, the abnormality degree calculation equation f(p) is as follow.
[Equation 2]
f(p)=min(r(p,X1),r(p,X1), . . . ,r(p,Xn)) (Equation 2)
Here r: distance calculation equation, Xn: nth center of gravity.
The distance calculation equation r (p, Xn) is defined by, for example, a linear distance in orthogonal coordinates.
The effects of the above configuration are as follows.
(1) If the data set P is sufficient, the cluster center of gravity X is automatically calculated by the cluster classifying unit 71 and the cluster center-of-gravity position calculating unit 72. Further, it is possible to quantitatively define the distribution of the data set P, that is, the state when the driving target 4 is normal, by the cluster center of gravity X.
(2) Based on the cluster center of gravity X, it is possible to detect the change in distribution of the data set P, that is, the occurrence of abnormality of the driving target 4.
In this way, by including the cluster classifying unit 71, the cluster center-of-gravity position calculating unit 72, and the abnormality degree calculation equation calculating unit 73, it is possible to detect the occurrence of abnormality of the driving target 4, without requiring any adjustment work.
Filing Document | Filing Date | Country | Kind |
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PCT/JP2016/054773 | 2/19/2016 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2017/141411 | 8/24/2017 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
8947028 | Gu | Feb 2015 | B2 |
10020769 | Arabackyj | Jul 2018 | B2 |
Number | Date | Country |
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5-236795 | Sep 1993 | JP |
9-113038 | May 1997 | JP |
2006-352988 | Dec 2006 | JP |
4221307 | Feb 2009 | JP |
2012-50155 | Mar 2012 | JP |
Entry |
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International Search Report (PCT/ISA/210) issued in PCT Application No. PCT/JP2016/054773 dated May 17, 2016 with English translation (two (2) pages). |
Japanese-language Written Opinion (PCT/ISA/237) issued in PCT Application No. PCT/JP2016/054773 dated May 17, 2016 (three (3) pages). |
Number | Date | Country | |
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20190052214 A1 | Feb 2019 | US |