CN114035140A - Fault detection and fault-tolerant control method for current sensor of induction motor - Google Patents
Fault detection and fault-tolerant control method for current sensor of induction motor Download PDFInfo
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Abstract
The invention discloses a fault detection and fault tolerance control method for a current sensor of an induction motor, which comprises the following steps: s1, calculating the absolute values of the third-level difference values of the alpha and beta axis currents before rotation and the beta axis current value after rotation of the alpha-beta coordinate system; s2, comparing the absolute value of the third-stage differential value with a threshold value, and setting the differential flag bit if the absolute value exceeds the threshold value; s3, if the differential flag bit is set, the current sensor has a fault; s4, detecting and recording the duration time that the current difference value between the current and the current in the last sampling period is 0 after setting the flag bit; s5, if the recording time exceeds a threshold value, reporting a sensor fault; and S6, after the fault of the sensor is reported, estimating the current value under the alpha-beta coordinate system before and after rotation by referring to the given value of the current of the d axis and the q axis, and replacing the current with the problem. The differential method used by the invention has high sensitivity and can detect the instantaneous change of the current caused by the fault of the sensor. The invention adds a delay algorithm to avoid false alarm faults, and the detection scheme is simple, accurate and reliable.
Description
Technical Field
The invention relates to the field of sensor fault detection, in particular to a fault detection and fault-tolerant control method for a current sensor of an induction motor.
Background
In recent years, an Induction Motor Drive (IMD) system breaks through the limitation of a complicated nonlinear control structure, and becomes the most widely applied motor type in the fields of electric locomotives, heating, ventilation, air conditioning, household appliances and the like. Once the current feedback value of the motor is abnormal, the whole control system adopting vector control cannot normally operate. To this end, some scholars and researchers are concerned with fault diagnosis and fault-tolerant control of some important sensors so that a fault of a sensor can be immediately judged at the moment when the fault occurs, and substitute values of sensor feedback values are obtained by other means while isolating the fault sensor signal to achieve normal operation of the system. In many existing motor control systems, three motor current sensors are used, and therefore most of the motor current sensors are subjected to fault diagnosis by the three sensors. However, in some severe environments, in order to improve the reliability of the operation of the system or to reduce the construction cost of the whole system, two current sensors are generally adopted, and the kirchhoff's current law is utilized to obtain the third-phase current.
The current detection mode based on the observer is to observe the motor current by using the observer, and compare the observed motor current signal with a signal detected and fed back by the sensor to judge whether the sensor is abnormal. However, the observer depends on the system model and system parameters, the accuracy of the model affects the observation result of the observer to some extent, and the measurement noise may cause the observation result of the observer to deviate to some extent.
Another detection mode is a knowledge-based detection mode: including expert systems, fuzzy theory, artificial neural networks, and the like. By applying various artificial intelligence techniques (symbolic intelligence or computational intelligence) to the analysis of historical data of an industrial process, hidden key data of the system can be extracted. However, these methods require a priori knowledge and a large amount of historical data in detecting and diagnosing faults.
Disclosure of Invention
The invention provides a fault detection and fault-tolerant control method for a current sensor of an induction motor, which aims to overcome the problems. On the basis of only two motor current sensors, the invention extracts relevant information from the signals of the fault sensors based on a method for detecting signal analysis, and detects the faults of the current sensors by using a detection mode of a three-level difference operator and a delay algorithm. Meanwhile, a fault part of a sensor feedback signal is constructed and replaced by a reference given signal of the system, so that the normal operation of the system after the fault sensor signal is isolated is realized, and the fault judgment is performed only under the condition that the current sensor signal is completely lost.
The invention comprises the following steps:
s1, converting the feedback values of the two-phase current sensors of the motors a and b into corresponding alpha and beta axis current values according to a Clark conversion principle; rotating the alpha-beta coordinate system by 120 degrees anticlockwise, and calculating a beta axis current value corresponding to the feedback value of the a-phase current sensor and the b-phase current sensor in the anticlockwise rotated coordinate system;
s2, a three-stage difference algorithm is provided for detecting the current sensor abnormality immediately when the fault occurs. Calculating the absolute values of the third-stage difference values of the alpha-axis current and the beta-axis current before rotation and the beta-axis current after rotation of the alpha-beta coordinate system in the S1 according to the calculation formula of the three-stage difference operator;
s3, comparing the absolute value of the third-stage difference value obtained in the step S2, namely the pulse amplitude at the fault moment, with a set threshold value, and judging the fault initial moment of the two-phase current sensor according to the comparison result; the threshold value is set according to experience;
at the initial time of the fault in S4 and S3, the differential flag bit of the fault of the current sensor is set, which indicates that the fault of the current sensor exists at the moment;
s5, in order to prevent the false alarm of the fault in S4, a delay algorithm is provided, after setting a differential flag bit, the duration that the difference value between the current motor current of the a-phase current sensor and the current motor current of the b-phase current sensor and the current motor current of the last sampling period is 0 is detected and recorded;
s6, if the recording time of S5 exceeds a set threshold, the locomotive display screen reports the corresponding sensor fault;
s7, when the locomotive reports the sensor fault, the current signal fed back to the control system by the corresponding current sensor can not be adopted any more, and in order to ensure that the control can continue to operate stably, the wrong alpha or beta axis current signal is replaced; the given value of the controller is used as a replacement value of an abnormal feedback value after being converted, namely, according to a reverse Park conversion principle, a current estimated value under an alpha-beta axis is obtained by using a d-q axis current given value under a two-phase rotating coordinate, and an abnormal value of an alpha or beta axis current is selectively replaced according to a specific fault type.
Further, the current sensor fault judgment in S1 is different from the conventional current sensor fault judgment in that a three-phase current feedback value is required, and the method only uses two current sensor feedback values.
Further, in S1, before the alpha-beta coordinate system rotates, the beta axis coincides with the a axis, and after the alpha-beta coordinate system rotates 120 degrees anticlockwise, the beta axis coincides with the b axis; therefore, two different Clark transformation matrixes can be obtained, and the two matrixes are integrated to realize decoupling on the fault corresponding relation between the a-axis current and the b-axis current and between the alpha-axis current and the beta-axis current.
Further, in S1, the current calculation formulas of the α axis and the β axis after the card transformation are given by the coincidence of the β axis and the a axis and the b axis, respectively, are:
wherein iasRepresenting a-axis motor stator current, ibsRepresenting the stator current of the b-axis motor; i.e. iαsRepresenting the current of the alpha axis after Clark transformation, iβsRepresents the current of the beta axis after Clark transformation;
after the alpha-beta coordinate system rotates 120 degrees anticlockwise, the current calculation formulas of the alpha axis and the beta axis are as follows:
wherein, i'αsTo representCurrent i 'after Clark conversion after 120-degree rotation of alpha axis'βsRepresents the current after Clark transformation after the beta axis rotates 120 degrees.
Further, a new current fault judgment method is adopted in S2, that is, even if a current signal generates a small instantaneous change, the differential values of its different stages will generate a pulse with a high amplitude; and the amplitude of the pulse generated by the third differential operation is much higher than that generated by the other differential operations.
Further, in S2, the current when the current signal changes slightly is set to be the current at the time t0, the current in the next cycle is set to be the current at the time t1, and so on. The first-order difference value is the difference between the value of the next period and the value of the previous period, the second-order difference value is the difference of the first-order difference value, and so on. The third-stage differential value is far larger than the first-stage differential value, so that the fault judgment can be based on the third-stage differential value.
Further, the delay algorithm in S5 is used to prevent false alarm;
the delay algorithm comprises:
comparing the sinusoidal phase current signal measured by the current sensor with the delay signal thereof, and reading the instantaneous current value measured by the current sensor;
reading another instantaneous current value in the next sampling period;
the absolute value calculation formula of the current value deviation of adjacent sampling periods is as follows:
Index_i＝|i-idelay| (3)
wherein i represents a current value; i.e. idelayRepresenting the current value before the last week; index _ i represents the absolute value of the current value deviation for adjacent sampling periods.
Index _ i, which is a deviation value of 0 in absolute value for a time period exceeding the set value, reports a current sensor fault.
Further, the step of calculating the estimated value of the α - β axis current from the Park inverse transformation matrix and the d-and q-axis given reference values in S7 includes:
1) the beta axis coincides with the a axis:
2) the beta axis coincides with the b axis:
wherein the content of the first and second substances,
representing a d-axis current setpoint;
representing a q-axis current setpoint; i.e. iαs_estRepresenting a first estimated value of the alpha axis calculated from a given value; i.e. iβs_estRepresenting a first estimate of the beta axis calculated from the given value;
i′αs_estrepresenting a second estimated value of the alpha axis calculated from the given value after 120 ° of counterclockwise rotation; i'βs_estRepresents a second estimate of the beta axis calculated from the given value after 120 ° counterclockwise rotation; thetaeIndicating the synchronization angle.
The difference method used by the invention has high sensitivity and can detect the instantaneous change of the current caused by the fault of the sensor. Meanwhile, the delay algorithm is added in the invention, so that the fault of false alarm can be avoided. The detection scheme does not need any estimation and is simple, accurate and reliable.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the steps of the present invention;
FIG. 2 is a schematic diagram of Clark transformation under the coincidence of the beta axis and the a axis of the present invention;
FIG. 3 is a schematic diagram of Clark transformation under the coincidence of the beta axis and the b axis of the present invention;
FIG. 4 is a schematic diagram of inverse Park transformation under coincidence of the β axis and the a axis of the present invention;
FIG. 5 is a schematic diagram of inverse Park transformation under coincidence of the β axis and the b axis according to the present invention;
FIG. 6 is a block diagram of a vector control system of the present invention;
FIG. 7 is a flow chart of the fault determination of the present invention
FIG. 8 is a current diagram of a phase A motor of the present invention;
FIG. 9 is a third stage difference value plot of the present invention;
FIG. 10 is a mark location bitmap of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. 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.
FIG. 6 is a block diagram of vector control according to the present invention, wherein usqCompensating the voltage for the q-axis; u. ofsdCompensating the voltage for the d-axis; u. ofsdcIs the d-axis feed forward voltage; u. ofsqcIs the q-axis feed forward voltage;
a q-axis output voltage;
d-axis output voltage;
outputting voltage for a shaft a;
is betaA shaft output voltage;
for flux linkage given value omegaslIs slip frequency; t isrIs the rotor time constant; l ismThe mutual inductance value of the motor is obtained; p is the number of pole pairs of the motor;
as shown in fig. 1 to 10, the present invention includes the following steps:
s1, according to Clark transformation principle, firstly collecting stator currents of a two-phase motor a and b, and respectively calculating i by using motor currents fed back by a two-phase current sensor a and b under two alpha-beta coordinate systems with 120 degrees of differenceαs、iβs、i′βsA value of (d);
1) when the beta axis coincides with the a axis:
that is to say that the first and second electrodes,
wherein iαsAnd iβsThe coordinate transformation relationship is shown in fig. 2, wherein the alpha and beta components of the stator current are when the beta axis is coincident with the a axis.
As can be seen from equation (1), the α -axis current depends on both the a-phase and b-phase currents. While the beta axis current depends on the a-phase current. This means that there is an abnormality in both the α -axis and β -axis currents for the a-phase current sensor failure. However, if the b-phase current sensor fails, only the α -axis current is abnormal, while the β -axis current remains normal.
2) When the beta axis coincides with the b axis:
that is to say that the first and second electrodes,
wherein, i'αsAnd i'βsThe coordinate transformation relationship is shown in fig. 3, which is the alpha and beta components of the stator current when the beta axis is coincident with the b axis.
As can be seen from (2), the α -axis current depends on two phase currents. However, the β -axis current depends only on the b-phase current. Therefore, if the a-phase current sensor fails, only the α -axis current is abnormal. However, if the b-phase current sensor fails, both the α -axis and β -axis currents will be abnormal.
As can be seen from the above analysis, it is possible to judge i in the formula (1)βsAnd judging whether the a-phase current sensor is normal or not according to the abnormality. If the phase a is normal, the formula (1) can be expressed as i in the same coordinate systemαsTo judge whether the b-phase current sensor is normal. If a is abnormal, the i 'in the coordinate system after rotation in the formula (2) is utilized'βsTo judge whether the b-phase current sensor is normal. On the contrary, whether the b-phase current sensor is normal or not can be judged by the formula (2), and then whether the a-phase current sensor is normal or not can be judged by the formula (2) or the formula (1).
S2 and S1 show that the currents of the a and b axes have a linear correspondence with the currents of the a and β axes, and thus the abnormality of the current sensors of the a and b phases can be indirectly determined by determining whether the currents of the a and β axes are abnormal. In order to detect the current abnormity acutely, the invention provides a novel method of three-stage difference operators. According to the method, when the signal is 0 off, the pulse amplitude generated by the third differential operation is far higher than the pulse amplitudes generated by other differential operations, so that fault judgment can be performed.
On the basis of S1, i is first calculatedβsIf the absolute value of the third-stage differential value is smaller than the set threshold value, the a-phase current sensor is normal, and the corresponding value of the rotated coordinate system does not need to be calculated at the moment, and i is directly utilizedαsThe absolute value of the differential value of the third stage can judge whether the b-phase current sensor is abnormal. If the absolute value is greater than the set threshold value, i 'in the rotated coordinate system is calculated'βsThe absolute value of the third-stage difference value of (a) is used to determine the b-phase current sensor.
Specifically, the calculation method of the third-stage difference value is as follows:
setting a current signal to slightly change at the time t0, and recording a current value at the time; the current values for three consecutive sampling periods are then recorded in sequence. The first-order difference value is the difference value between the value of the next period and the value of the previous period, and the current values of the four sampling periods can obtain three first-order difference values; the second-order differential value is the differential value of the first-order differential value, and then the three first-order differential values obtain two second-order differential values; the third-level differential value is a differential value of the second-level differential value, and then the two second-level differential values obtain a third-level differential value.
The calculation formula is shown in Table 1, in which i isαsFor example.
TABLE 1 three-level differential operator calculation
S3, judging the initial time of the two-phase current sensor fault according to the comparison result of the absolute value of the third-stage differential value and the set threshold value, and setting the fault differential flag bit of the current sensor to indicate that a current sensor fault possibly exists at the moment, but the possibility of false alarm of the fault caused by interference is not eliminated;
that is, the result calculated in S2 is compared with the set threshold value:
and if the absolute value of the difference value is larger than the set threshold, setting the difference flag bit.
Wherein, Delta3iαsIs iαsThe third-order differential value of (a),
is a threshold value obtained from engineering experience.
S4, a delay algorithm is proposed to prevent the setting of the differential flag bit in S3 from being caused by interference. The method compares the sinusoidal phase current signal measured by the current sensor with its delayed signal. Assume that when t is 0, the instantaneous current value measured by the current sensor is read and stored in a variable named Cur _ t 0. Then, in the next sampling period, another instantaneous current value is read and stored in the variable Cur _ t 1. At this time, Cur _ t1 is the current value of the sinusoidal current, and Cur _ t0 is the value of its delay signal. Under normal conditions, the value of Cur _ t1 is always different from the value of Cur _ t0 at any time. If the measurement signal is completely lost, all current sensor signals become zero, and all stored present and delayed signals are also zero; or the current sampling signal and the delayed signal thereof are the same constant value. I.e. the absolute value of the current value deviation for adjacent sampling periods is 0.
Specifically, after the differential flag bit is set in S3, the time during which the absolute value of the difference between the current motor current and the motor current in the previous sampling period continues to be 0 is detected and recorded, and if the recorded time exceeds a set threshold, a corresponding sensor fault is reported.
That is, Index _ i ═ i-idelay| (4)
if(Index_i＝＝0){Cur_Counter++；}
f(Cur_Counter＞Cur_Coe) (5)
{FCur_Flg＝1；}
Wherein i represents a current value; i.e. idelayRepresenting the current value before the last week; index _ i represents the absolute value of the current value deviation of adjacent sampling periods; cur _ Counter represents a Counter with the absolute value of the difference being 0; cur _ Coe represents a time threshold; fCur_FlgIndicating a fault flag. The failure determination process can be seen in fig. 7.
And S5, when the current sensor reports a sensor fault, the feedback sampling value cannot be adopted due to abnormality, and alpha and beta currents obtained by performing reverse Park conversion on the reference given values of the d axis and the q axis are adopted to maintain the normal operation of the control system.
1) When the beta axis coincides with the a axis:
the coordinate transformation relationship is shown in fig. 4.
2) When the beta axis coincides with the b axis:
the coordinate transformation relationship is shown in fig. 5.
By the equations (6) and (7), estimated values of α and β currents can be calculated.
According to the formula (1), when the a-phase current sensor fails, both the α and β currents are abnormal; when the b-phase current sensor fails, only the α -axis current is abnormal, while the β -axis current remains normal.
According to the formula (2), when the a-phase current sensor fails, only the α -axis current is abnormal; when the b-phase current sensor fails, both the α -axis and β -axis currents are abnormal.
In view of the above, it can be seen that,
1) when the a-phase current sensor is failed and the b-phase current sensor is normal, the α and β currents calculated by equation (1) are both abnormal, while the β -axis current in equation (2) is normally available, i.e. only the α -axis needs to be replaced.
2) When the a-phase current sensor is normal and the b-phase current sensor is failed, the α and β currents calculated by equation (2) are both abnormal, while the β -axis current in equation (1) is normally available, i.e., only the α -axis needs to be replaced.
3) When the phase a and phase b current sensors are in failure, both the alpha and beta shafts need to be replaced;
4) when the phase current sensors of the a and b phases are normal, the alpha and beta axes do not need to be replaced;
specifically, the current substitutions for different current sensor faults are shown in table 2.
TABLE 2 Fault tolerant control Current selection
| a-phase current sensor | b-phase current sensor | Current selection |
| Is normal | Is normal | ias iβs |
| Is normal | Abnormality (S) | ias_est iβs |
| Abnormality (S) | Is normal | i′as_est i′βs |
| Abnormality (S) | Abnormality (S) | ias_est iβs_est |
According to the execution cycle 400us of a real program, the fault of the current sensor of the phase a motor is randomly selected to carry out matlab simulation.
To show the generality of the fault occurrence, the a-phase motor current is changed to 0 at 0.9s randomly selected in the simulation, as shown in fig. 8. At this time, the difference value | Δ of the third stage which can be calculated is corresponded3iβsShown in figure 9. The value is much larger than the first two differential values, the threshold is set to 1.2A, and the corresponding differential flag is set, as shown in fig. 10. After a delay of some time (0.4s) the fault bit is set, reporting a current sensor fault.
As can be seen from the simulation results, the differential method has high sensitivity and can immediately detect the transient current change caused by the fault of the current sensor. Meanwhile, the delay algorithm is added, so that the fault of false alarm can be avoided.
Has the advantages that:
the difference method used by the invention has high sensitivity and can detect the instantaneous change of the current caused by the fault of the sensor. Meanwhile, the delay algorithm is added in the invention, so that the fault of false alarm can be avoided. The detection scheme has the characteristics of simplicity, accuracy, reliability and the like.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A fault detection and fault-tolerant control method for a current sensor of an induction motor is characterized by comprising the following steps:
s1, converting the feedback values of the two-phase current sensors of the motors a and b into corresponding alpha and beta axis current values according to a Clark conversion principle; rotating the alpha-beta coordinate system by 120 degrees anticlockwise, and calculating a beta axis current value corresponding to the feedback value of the a-phase current sensor and the b-phase current sensor in the anticlockwise rotated coordinate system;
s2, a three-stage difference algorithm is provided for detecting the current sensor abnormality immediately when the fault occurs. Obtaining absolute values of third-stage difference values of alpha and beta axis currents before rotation and beta axis current values after rotation of an alpha-beta coordinate system in S1 according to a calculation formula of a three-stage difference operator;
s3, comparing the absolute value of the third-stage difference value calculated in the S2, namely the pulse amplitude at the fault moment, with a set threshold value, and judging the fault initial moment of the two-phase current sensor according to the comparison result; the threshold value is set according to experience;
at the initial time of the fault in S4 and S3, the differential flag bit of the fault of the current sensor is set, which indicates that the fault of the current sensor exists at the moment;
s5, in order to prevent the false alarm of the fault in S4, a delay algorithm is provided, after setting a differential flag bit, the duration that the difference value between the current motor current of the a-phase current sensor and the current motor current of the b-phase current sensor and the current motor current of the last sampling period is 0 is detected and recorded;
s6, if the recording time of S5 exceeds a set threshold, the locomotive display screen reports the corresponding sensor fault;
and S7, as stated in S6, when the locomotive reports the sensor fault, the current signal fed back to the control system by the corresponding current sensor can not be adopted any more, and at this time, in order to ensure that the control can continue to operate stably, the abnormal alpha or beta axis current signal needs to be replaced. The method uses the given value of the controller as a replacement value of the abnormal feedback value after being converted, namely, according to the inverse Park conversion principle, the current estimated value under the alpha-beta axis is obtained by using the given value of the current of the d-q axis under the two-phase rotating coordinate, and the abnormal value of the current of the alpha or beta axis is selectively replaced according to the specific fault type.
2. The method of claim 1, wherein the current sensor fault determination in S1 is different from a method of a conventional current sensor fault determination that requires three-phase current feedback values, and only two current sensor feedback values are used.
3. The method of claim 1, wherein the β axis coincides with the a axis before the α - β coordinate system is rotated in S1, and the β axis coincides with the b axis after the α - β coordinate system is rotated 120 ° counterclockwise. Therefore, two different Clark transformation matrixes can be obtained, and by combining the two matrixes, the decoupling of the fault corresponding relation between the a-axis current and the b-axis current and the alpha-axis current and the beta-axis current can be realized.
4. The method according to claim 3, wherein the current calculation formulas of the α axis and the β axis after the Cark transformation under the condition that the β axis coincides with the a axis and the b axis respectively are as follows:
wherein iasRepresenting a-axis motor stator current, ibsRepresenting the stator current of the b-axis motor; i.e. iαsRepresenting the current of the alpha axis after Clark transformation, iβsRepresents the current of the beta axis after Clark transformation;
after the alpha-beta coordinate system rotates 120 degrees anticlockwise, the current calculation formulas of the alpha axis and the beta axis are as follows:
wherein, i'αsDenotes the current i 'of alpha shaft rotated by 120 DEG and subjected to Clark conversion'βsRepresents the current after Clark transformation after the beta axis rotates 120 degrees.
5. The method as claimed in claim 1, wherein a new current fault determination method is adopted in S2, that is, even if the current signal has a slight transient variation, the differential values of different stages will generate a pulse with high amplitude; the pulse amplitude generated by the third differential operation is far higher than the pulse amplitudes generated by other differential operations, and can be used as a basis for fault judgment.
6. The method as claimed in claim 5, wherein the current signal is a current at time t0 when the current signal changes slightly, the current at time t1 is a current in the next cycle, and so on, wherein the first-order difference value is a difference between a value in the next cycle and a value in the previous cycle, the second-order difference value is a difference between the first-order difference values, and so on.
7. The method for fault detection and fault-tolerant control of an induction motor current sensor according to claim 1, wherein the delay algorithm in S5 is used for preventing false fault alarm;
the delay algorithm comprises:
comparing the sinusoidal phase current signal measured by the current sensor with the delay signal thereof, and reading the instantaneous current value measured by the current sensor;
reading another instantaneous current value in the next sampling period;
the absolute value calculation formula of the current value deviation of adjacent sampling periods is as follows:
Index_i＝|i-idelay| (3)
wherein i represents a current value; i.e. idelayRepresenting the current value before the last week; index _ i represents the absolute value of the current value deviation of adjacent sampling periods;
index _ i, which is a deviation value of 0 in absolute value for a time period exceeding the set value, reports a current sensor fault.
8. The method of claim 1, wherein the step of calculating the estimated value of the α - β axis current from the inverse Park transformation matrix and the given reference values of the d and q axes in S7 comprises:
1) the beta axis coincides with the a axis:
2) the beta axis coincides with the b axis:
wherein the content of the first and second substances,
representing a d-axis current setpoint;
representing a q-axis current setpoint; i.e. iαs_estRepresenting a first estimated value of the alpha axis calculated from a given value; i.e. iβs_estRepresenting a first estimate of the beta axis calculated from the given value;
i′αs_estrepresenting a second estimated value of the alpha axis calculated from the given value after 120 ° of counterclockwise rotation; i'βs_estRepresents a second estimate of the beta axis calculated from the given value after 120 ° counterclockwise rotation; thetaeIndicating the synchronization angle.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114859282A (en) * | 2022-06-02 | 2022-08-05 | 南京航空航天大学 | Double salient pole motor current sensor signal loss fault diagnosis method |
| CN117492355A (en) * | 2023-12-28 | 2024-02-02 | 天津英联石油设备技术服务有限公司 | Automatic control system with redundant fault tolerance function and control method |
| CN117783629A (en) * | 2023-04-13 | 2024-03-29 | 国网江苏省电力有限公司电力科学研究院 | High fault tolerance system and control method of optical fiber current sensor suitable for energy industry |
| CN117783629B (en) * | 2023-04-13 | 2024-05-31 | 国网江苏省电力有限公司电力科学研究院 | High fault tolerance system and control method of optical fiber current sensor suitable for energy industry |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003255006A (en) * | 2002-03-06 | 2003-09-10 | Nissan Motor Co Ltd | Current sensor fault sensing device for ac motor |
| CN104122479A (en) * | 2014-07-29 | 2014-10-29 | 华中科技大学 | Online detection method for open-circuit faults of power tubes of induction-motor vector control system |
| CN107015185A (en) * | 2017-05-03 | 2017-08-04 | 北京新能源汽车股份有限公司 | A kind of detection method of current sensor faults, device and automobile |
| CN110794302A (en) * | 2019-10-31 | 2020-02-14 | 东南大学 | Zero drift fault diagnosis method for current sensor of permanent magnet linear motor |
| CN113395030A (en) * | 2021-06-21 | 2021-09-14 | 珠海格力电器股份有限公司 | Control device and method of motor driving system and motor |
-
2021
- 2021-11-19 CN CN202111400083.XA patent/CN114035140B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003255006A (en) * | 2002-03-06 | 2003-09-10 | Nissan Motor Co Ltd | Current sensor fault sensing device for ac motor |
| CN104122479A (en) * | 2014-07-29 | 2014-10-29 | 华中科技大学 | Online detection method for open-circuit faults of power tubes of induction-motor vector control system |
| CN107015185A (en) * | 2017-05-03 | 2017-08-04 | 北京新能源汽车股份有限公司 | A kind of detection method of current sensor faults, device and automobile |
| CN110794302A (en) * | 2019-10-31 | 2020-02-14 | 东南大学 | Zero drift fault diagnosis method for current sensor of permanent magnet linear motor |
| CN113395030A (en) * | 2021-06-21 | 2021-09-14 | 珠海格力电器股份有限公司 | Control device and method of motor driving system and motor |
Non-Patent Citations (1)
| Title |
|---|
| 马雷;陈宇航;张云峰;: "基于坐标变换的永磁同步电机电流传感器容错控制", 电机与控制应用, no. 11 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114859282A (en) * | 2022-06-02 | 2022-08-05 | 南京航空航天大学 | Double salient pole motor current sensor signal loss fault diagnosis method |
| CN114859282B (en) * | 2022-06-02 | 2023-04-18 | 南京航空航天大学 | Double salient pole motor current sensor signal loss fault diagnosis method |
| CN117783629A (en) * | 2023-04-13 | 2024-03-29 | 国网江苏省电力有限公司电力科学研究院 | High fault tolerance system and control method of optical fiber current sensor suitable for energy industry |
| CN117783629B (en) * | 2023-04-13 | 2024-05-31 | 国网江苏省电力有限公司电力科学研究院 | High fault tolerance system and control method of optical fiber current sensor suitable for energy industry |
| CN117492355A (en) * | 2023-12-28 | 2024-02-02 | 天津英联石油设备技术服务有限公司 | Automatic control system with redundant fault tolerance function and control method |
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