阅读说明：本技术 永磁电机驱动系统电流传感器故障类型识别方法及装置 (Method and device for identifying fault type of current sensor of permanent magnet motor driving system ) 是由 马光同 张晗 徐帅 任冠州 孙振耀 姚春醒 于 2021-08-31 设计创作，主要内容包括：本发明公开了一种永磁电机驱动系统电流传感器故障类型识别方法及装置,该方法包括采集永磁电机的三相定子电流信号和永磁电机转子的位置信号；根据采集的三相定子电流信号和dq轴参考电流信号,定位故障电流传感器；对故障电流传感器采集的相电流值进行采样,构建故障识别变量；根据构建的故障识别变量对电流传感器故障类型进行识别。本发明解决了在变频调速系统中,单一使用基于模型的故障诊断方法仅能定位故障传感器不能确定故障类型的通用性问题,不需要借助额外设备即可准确识别出电流传感器的断线故障、卡死故障、增益故障和偏置故障四种典型故障类型,有较强的鲁棒性,同时该方法可以和任意基于模型的电流传感器故障诊断方法相结合。(The invention discloses a method and a device for identifying the fault type of a current sensor of a permanent magnet motor driving system, wherein the method comprises the steps of collecting three-phase stator current signals of a permanent magnet motor and position signals of a permanent magnet motor rotor; positioning a fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals; sampling phase current values acquired by a fault current sensor to construct a fault identification variable; and identifying the fault type of the current sensor according to the constructed fault identification variable. The method solves the problem that the universality that the fault type can not be determined only by positioning the fault sensor by using a fault diagnosis method based on a model singly in a variable frequency speed control system, can accurately identify four typical fault types of disconnection fault, blocking fault, gain fault and offset fault of the current sensor without additional equipment, has stronger robustness, and can be combined with any fault diagnosis method of the current sensor based on the model.)

1. A method for identifying the fault type of a current sensor of a permanent magnet motor driving system is characterized by comprising the following steps:

s1, collecting three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

s2, positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

s3, sampling phase current values acquired by the fault current sensor, and constructing fault identification variables;

and S4, identifying the fault type of the current sensor according to the constructed fault identification variable.

2. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 1, wherein the step S1 specifically comprises the following sub-steps:

s1-1, collecting stator current signals of any two phases of the permanent magnet motor, and calculating stator current signals of a third phase by using kirchhoff current law;

and S1-2, acquiring a real-time speed signal and an angle signal of the permanent magnet motor rotor.

3. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 1, wherein the step S2 specifically comprises:

s2-1, driving and controlling the permanent magnet motor by adopting a permanent magnet synchronous motor model prediction current control method;

s2-2, calculating a q-axis reference current signal under a dq rotation coordinate system according to the real-time speed signal and the set reference speed signal of the permanent magnet motor rotor; setting a d-axis reference current signal to be 0;

and S2-3, positioning the fault current sensor by adopting a current sensor fault positioning method based on coordinate transformation according to the three-phase stator current signal and the dq-axis reference current signal.

4. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 3, wherein the driving control of the permanent magnet motor by adopting the permanent magnet synchronous motor model prediction current control method specifically comprises:

establishing a mathematical model of the permanent magnet motor and a driving current transformation system thereof;

discretizing the mathematical model of the permanent magnet motor and the driving current transformation system of the permanent magnet motor, establishing a discretization stator current prediction model under a rotating coordinate system, and predicting the current value of the permanent magnet motor at the next moment after one-step compensation is carried out on the system time delay;

and establishing a cost function according to the tracking current error, determining the switching state, and outputting and controlling the on-off of the switching tube of the inverter.

5. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 3, wherein the mathematical model of the permanent magnet motor and the driving converter system thereof is represented as follows:

wherein u is_d、u_qIs the stator voltage in dq axis, R_SIs stator winding resistance, i_d、i_qStator current in dq axis, L_d、L_qStator inductance, ω, under dq axis_eFor the electrical angle, psi, of the permanent-magnet machine_fIs a permanent magnet flux linkage, T_eFor electromagnetic torque of the machine, p_nThe number of pole pairs of the motor is shown.

6. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 5, wherein the discretization processing is performed on the established mathematical model of the permanent magnet motor, and a discretization stator current prediction model under a rotating coordinate system is established, specifically:

discretizing the mathematical model of the permanent magnet motor and the driving current transformation system thereof by adopting a first-order forward Euler method, and establishing a discretization stator current prediction model under a rotating coordinate system, wherein the discretization stator current prediction model is expressed as

Wherein i_d(k+1)、i_q(k +1) represents a predicted value of the dq-axis stator current at the sampling time k +1, i_d(k)、i_q(k) Representing the dq-axis stator current sample value u at the current k sample time_d(k)、u_q(k) Representing the dq-axis stator voltage sample value, T, at the current k sample time_sRepresenting the sampling period.

7. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 3, wherein the positioning of the fault current sensor by using the current sensor fault positioning method based on coordinate transformation specifically comprises:

calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta a coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta b coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

and comparing the absolute value of the residual error of the alpha-axis current in the alpha-beta alpha coordinate system and the absolute value of the residual error of the alpha-axis current in the alpha-beta b coordinate system with a set residual error threshold value to obtain a positioning result of the fault current sensor.

8. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 1, wherein the step S3 specifically comprises the following sub-steps:

s3-1, sampling phase current values acquired by a fault current sensor to obtain phase current values of all sampling points in a phase current period;

s3-2, all samples are collected in one phase current periodCalculating the sum S of the phase current values of all sampling points by the phase current values of the sampling points_xIs shown as

Wherein i_x(N) is the phase current value of the nth sampling point in one phase current period, and N is the number of sampling points in one phase current period;

s3-3, sampling after deriving the phase current value acquired by the fault current sensor to obtain phase current derivative values of all sampling points in a phase current period;

s3-4, calculating the sum d of phase current derivative values of any two continuous sampling points_x(n) is represented by

d_x(n)＝i′_x(n)+i′_x(n-1)

Wherein, i'_x(n) is the current derivative value at the n sampling point in one phase current cycle, where i'_x(n-1) is the current derivative value of the (n-1) th sampling point in one phase current period;

s3-5, calculating the sum S of the phase current values_xSum of derivative values of sum phase currents d_x(n) constructing fault recognition variables (S)_x，d_x(n))。

9. The method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to claim 1, wherein the step S4 specifically comprises the following sub-steps:

s4-1, judging whether the sum of the phase current values of all sampling points in one phase current period is smaller than a set threshold value according to the constructed fault identification variable; if yes, go to step S4-2; otherwise, executing step S4-3;

s4-2, judging whether the sum of phase current derivative values of any two continuous sampling points in one phase current period is equal to zero or not; if yes, judging that the fault current sensor is a broken line fault; otherwise, judging the fault current sensor as a gain fault;

s4-3, judging whether the sum of phase current derivative values of any two continuous sampling points in one phase current period is equal to zero or not; if yes, judging the fault current sensor to be a stuck fault; otherwise, judging the fault current sensor to be a bias fault.

10. An apparatus for applying the method for identifying the fault type of the current sensor of the permanent magnet motor driving system according to any one of claims 1 to 9, comprising:

the data acquisition module is used for acquiring three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

the fault positioning module is used for positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

the diagnostic variable construction module is used for sampling phase current values acquired by the fault current sensor and constructing fault identification variables;

and the fault identification module is used for identifying the fault type of the current sensor according to the constructed fault identification variable.

Technical Field

The invention relates to the technical field of fault diagnosis of a current sensor in a speed regulating system, in particular to a method and a device for identifying fault types of the current sensor of a permanent magnet motor driving system.

Background

A permanent magnet motor drive system generally employs two or three current sensors to collect current information for closed-loop control of the system. The feedback signal of the current sensor is the basis of the current closed-loop control of the permanent magnet synchronous motor. When the current sensor fails, the performance of the control system deteriorates due to the inability to obtain correct current information. The types of faults of current sensors can be generally classified into four categories: disconnection faults, stuck-at faults, gain faults, and bias faults. Any type of current sensor failure affects the reliability of the system operation, and in addition, the ambiguity of the type of failure presents difficulties in the maintenance of the motor drive system. Therefore, in order to ensure fault-tolerant control and convenient maintenance of the system, not only fault location is carried out on the fault current sensor, but also the fault type of the fault sensor is accurately judged.

According to literature search, some signal-based fault diagnosis methods can determine partial fault types, but can only be effective under certain specific types of current sensor faults; although the fault diagnosis method based on the model can be applied to all types of current sensor faults, the fault type cannot be effectively distinguished; in the existing fault type detection method, at most three kinds of faults can be detected, and the detection method is not comprehensive enough.

Disclosure of Invention

Aiming at the defects in the prior art, the invention provides a method and a device for identifying the fault type of a current sensor of a permanent magnet motor driving system.

In order to achieve the purpose of the invention, the invention adopts the technical scheme that:

in a first aspect, the invention provides a method for identifying fault types of current sensors of a permanent magnet motor driving system, which comprises the following steps:

s1, collecting three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

s2, positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

s3, sampling phase current values acquired by the fault current sensor, and constructing fault identification variables;

and S4, identifying the fault type of the current sensor according to the constructed fault identification variable.

Further, the step S1 specifically includes the following sub-steps:

s1-1, collecting stator current signals of any two phases of the permanent magnet motor, and calculating stator current signals of a third phase by using kirchhoff current law;

and S1-2, acquiring a real-time speed signal and an angle signal of the permanent magnet motor rotor.

Further, the step S2 specifically includes:

s2-1, driving and controlling the permanent magnet motor by adopting a permanent magnet synchronous motor model prediction current control method;

s2-2, calculating a q-axis reference current signal under a dq rotation coordinate system according to the real-time speed signal and the set reference speed signal of the permanent magnet motor rotor; setting a d-axis reference current signal to be 0;

and S2-3, positioning the fault current sensor by adopting a current sensor fault positioning method based on coordinate transformation according to the three-phase stator current signal and the dq-axis reference current signal.

Furthermore, the driving control of the permanent magnet motor by using the permanent magnet synchronous motor model prediction current control method specifically includes:

establishing a mathematical model of the permanent magnet motor and a driving current transformation system thereof;

discretizing the established mathematical model of the permanent magnet motor, establishing a discretization stator current prediction model under a rotating coordinate system, and predicting the current value of the permanent magnet motor at the next moment after one-step compensation is carried out on system time delay;

and establishing a cost function according to the tracking current error, determining the switching state, and outputting and controlling the on-off of the switching tube of the inverter.

Further, the mathematical model of the permanent magnet motor and the driving converter system thereof is represented as follows:

wherein u is_d、u_qIs the stator voltage in dq axis, R_SIs stator winding resistance, i_d、i_qStator current in dq axis, L_d、L_qStator inductance, ω, under dq axis_eFor the electrical angle, psi, of the permanent-magnet machine_fIs a permanent magnet flux linkage, T_eFor electromagnetic torque of the machine, p_nThe number of pole pairs of the motor is shown.

Furthermore, the discretization processing is performed on the established mathematical model of the permanent magnet motor, and a discretization stator current prediction model under a rotating coordinate system is established, specifically:

discretizing the mathematical model of the permanent magnet motor and the driving current transformation system thereof by adopting a first-order forward Euler method, and establishing a discretization stator current prediction model under a rotating coordinate system, wherein the discretization stator current prediction model is expressed as

Wherein i_d(k+1)、i_q(k +1) represents a predicted value of the dq-axis stator current at the sampling time k +1, i_d(k)、i_q(k) Representing the dq-axis stator current sample value u at the current k sample time_d(k)、u_q(k) Representing the dq-axis stator voltage sample value, T, at the current k sample time_sRepresenting the sampling period.

Furthermore, the positioning of the fault current sensor by using the current sensor fault positioning method based on coordinate transformation specifically comprises the following steps:

calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta a coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta b coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

and comparing the absolute value of the residual error of the alpha-axis current in the alpha-beta a coordinate system and the absolute value of the residual error of the alpha-axis current in the alpha-beta b coordinate system with a set residual error threshold value to obtain a positioning result of the fault current sensor.

Further, the step S3 specifically includes the following sub-steps:

s3-1, sampling phase current values acquired by a fault current sensor to obtain phase current values of all sampling points in a phase current period;

s3-2, calculating the sum S of the phase current values of all sampling points according to the phase current values of all sampling points in one phase current period_xIs shown as

Wherein i_x(N) is the phase current value of the nth sampling point in one phase current period, and N is the number of sampling points in one phase current period;

s3-3, sampling after deriving the phase current value acquired by the fault current sensor to obtain phase current derivative values of all sampling points in a phase current period;

s3-4, calculating the sum d of phase current derivative values of any two continuous sampling points_x(n) is represented by

d_x(n)＝i′_x(n)+i′_x(n-1)

Wherein, i'_x(n) is the current derivative value at the n sampling point in one phase current cycle, where i'_x(n-1) is the current derivative value of the (n-1) th sampling point in one phase current period;

s3-5, calculating the sum S of the phase current values_xSum of derivative values of sum phase currents d_x(n) constructing fault recognition variables (S)_x，d_x(n))。

Further, the step S4 specifically includes the following sub-steps:

s4-1, judging whether the sum of the phase current values of all sampling points in one phase current period is smaller than a set threshold value according to the constructed fault identification variable; if yes, go to step S4-2; otherwise, executing step S4-3;

s4-2, judging whether the sum of phase current derivative values of any two continuous sampling points in one phase current period is equal to zero or not; if yes, judging that the fault current sensor is a broken line fault; otherwise, judging the fault current sensor as a gain fault;

s4-3, judging whether the sum of phase current derivative values of any two continuous sampling points in one phase current period is equal to zero or not; if yes, judging the fault current sensor to be a stuck fault; otherwise, judging the fault current sensor to be a bias fault.

In a second aspect, the present invention further provides an apparatus applying the method for identifying a fault type of a current sensor of a permanent magnet motor driving system, including:

the data acquisition module is used for acquiring three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

the fault positioning module is used for positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

the diagnostic variable construction module is used for sampling phase current values acquired by the fault current sensor and constructing fault identification variables;

and the fault identification module is used for identifying the fault type of the current sensor according to the constructed fault identification variable.

The invention has the following beneficial effects:

1. the invention solves the problem that the single fault diagnosis method based on the model can only position the fault sensor and can not determine the type of the fault in the variable frequency speed control system.

2. The invention can realize the identification of four fault types of disconnection fault, blocking fault, gain fault and bias fault of the sensor by analyzing the fault current characteristic without using additional equipment.

3. The method is not influenced by motor parameters, has strong robustness, and can be combined with any fault diagnosis method based on a model.

Drawings

Fig. 1 is a schematic flow chart of a method for identifying a fault type of a current sensor of a permanent magnet motor driving system according to the present invention;

FIG. 2 is a schematic block diagram of a permanent magnet motor drive system having two current sensors according to the present invention;

FIG. 3 is a schematic diagram of coordinate transformation of the current sensor fault location method based on coordinate transformation according to the present invention; wherein fig. 3(a) is a coordinate transformation when an α axis is coincident with an a axis in a three-phase coordinate system in an α - β a coordinate system, and fig. 3(b) is a coordinate transformation when an α axis is coincident with a b axis in a three-phase coordinate system in an α - β b coordinate system;

FIG. 4 is a diagram illustrating simulation results provided by the present invention; wherein FIG. 4(a) is a sample waveform for the A-phase current sensor; FIG. 4(b) shows the phase A current residual and its threshold waveform; FIG. 4(c) is d_x(n) a waveform; FIG. 4(d) is S_aAnd S_thA waveform; fig. 4(e) is an a-phase fault type code waveform.

Detailed Description

The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.

Example 1

As shown in fig. 1, embodiment 1 of the present invention provides a method for identifying a fault type of a current sensor of a permanent magnet motor drive system, including the following steps S1 to S4:

s1, collecting three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

in the present embodiment, step S1 specifically includes the following substeps S1-1 to S1-2:

s1-1, collecting stator current signals of any two phases of the permanent magnet motor, and calculating stator current signals of a third phase by using kirchhoff current law;

specifically, the method utilizes two current sensors to respectively acquire the A-phase stator current i of the permanent magnet traction motor_aAnd B-phase stator current i_bObtaining the C-phase stator current i by using kirchhoff's current law_cIs shown as

i_c＝-i_a-i_b

Optionally, the invention can also acquire the A-phase stator current i of the permanent magnet traction motor by using three current sensors respectively_aB phase stator current i_bAnd C-phase stator current i_c。

And S1-2, acquiring a real-time speed signal and an angle signal of the permanent magnet motor rotor.

Specifically, the invention utilizes the incremental photoelectric encoder to detect and obtain the real-time speed of the permanent magnet motor rotorSignal omega_mAnd angle signal theta_e。

S2, positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

in the present embodiment, step S2 specifically includes the following substeps S2-1 to S2-3:

s2-1, driving and controlling the permanent magnet motor by adopting a permanent magnet synchronous motor model prediction current control method;

specifically, the invention adopts a permanent magnet synchronous motor model prediction current control method to carry out drive control on a permanent magnet motor, and specifically comprises the following steps:

establishing a mathematical model of the permanent magnet motor and a driving current transformation system thereof;

specifically, in the present invention, for a permanent magnet motor driving system in which only two current sensors are installed and a motor is driven and controlled by using a model prediction current control method, as shown in fig. 2, mathematical models of a permanent magnet motor and a driving converter system thereof are established, and are expressed as

Wherein u is_d、u_qIs the stator voltage in dq axis, R_SIs stator winding resistance, i_d、i_qStator current in dq axis, L_d、L_qStator inductance, ω, under dq axis_eFor the electrical angle, psi, of the permanent-magnet machine_fIs a permanent magnet flux linkage, T_eFor electromagnetic torque of the machine, p_nThe number of pole pairs of the motor is;

discretizing the established mathematical model of the permanent magnet motor, establishing a discretization stator current prediction model under a rotating coordinate system, and predicting the current value of the permanent magnet motor at the next moment after one-step compensation is carried out on system time delay;

specifically, the invention adopts a first-order forward Euler method to carry out discretization treatment on the established mathematical model of the permanent magnet motor and the driving current transformation system thereof, and establishes a discretization stator current prediction model in a rotating coordinate system, which is expressed as

Wherein i_d(k+1)、i_q(k +1) represents a predicted value of the dq-axis stator current at the sampling time k +1, i_d(k)、i_q(k) Representing the dq-axis stator current sample value u at the current k sample time_d(k)、u_q(k) Representing the dq-axis stator voltage sample value, T, at the current k sample time_sRepresenting the sampling period.

In order to ensure the accuracy and real-time performance of a control system, the delay needs to be compensated, so the method carries out one-step compensation on the sampling delay and the control delay to obtain a dq-axis stator current predicted value at the sampling moment of k +2, which is expressed as

Wherein i_d(k+2)、i_q(k +2) represents a predicted value of the dq-axis stator current at the sampling time k +1, u_d(k+1)、u_q(k +1) represents a predicted value of the dq-axis stator voltage at the sampling time k + 1.

And establishing a cost function according to the tracking current error, determining the switching state, and outputting and controlling the on-off of the switching tube of the inverter.

Specifically, the present invention establishes a cost function J, expressed as

J＝(i_d(k)-i_d(+2))²+(i_q(k)-i_q(+2))²

After the total cost function is established, the inverter vector is preselected, all the current allowed switching states are exhausted by an enumeration method and brought into the cost function for calculation, the switching state which enables the cost function to be minimum is found out, and then the switching state is directly used as an inverter control signal to be input to control the on and off of a switching tube of the inverter.

S2-2, calculating a q-axis reference current signal under a dq rotation coordinate system according to the real-time speed signal and the set reference speed signal of the permanent magnet motor rotor; setting the d-axis reference current to be 0;

in particular, the invention is based on a real-time speed signal ω of a rotor of a permanent magnet motor_mAnd a set reference speed omega_m,refCalculating a q-axis reference current signal i in a dq rotation coordinate system by a rotating speed loop PI regulator_q,ref(ii) a While setting the d-axis reference current signal to 0.

And S2-3, positioning the fault current sensor by adopting a current sensor fault positioning method based on coordinate transformation according to the three-phase stator current signal and the dq-axis reference current signal.

Specifically, for a permanent magnet synchronous motor driving system driven by a two-level inverter, the invention adopts a current sensor fault positioning method based on coordinate transformation to position a fault current sensor, and the method specifically comprises the following steps:

calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta a coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

specifically, the α - β a coordinate system is a two-phase stationary coordinate system in which the positive direction of the α axis coincides with the positive direction of the phase winding of the motor a, and as shown in fig. 3(a), the measurement current component i of the α axis in the α - β a coordinate system is_αaMeasuring current i from phase A_aAnd B-phase measuring current i_bObtained by Clark transformation and is represented as

Estimated current component i of alpha axis under alpha-beta a coordinate system^* _αaEstimating the current i from the d-q axis in the control loop^* _dAnd i^* _qIs obtained by Park transformation and is expressed as

Measuring current component i according to alpha axis in alpha-beta a coordinate system_αaAnd estimating the current component i^* _αaCalculating the measured current component i_αaAnd estimating the current component i^* _αaAbsolute value of residual error of epsilon_aIs shown as

Calculating a measured current component and an estimated current component of an alpha axis under an alpha-beta b coordinate system by utilizing coordinate transformation according to the collected three-phase stator current signals and the dq axis reference current signals, and calculating a residual absolute value of the measured current component and the estimated current component;

specifically, the α - β B coordinate system is a two-phase stationary coordinate system in which the positive direction of the α axis coincides with the positive direction of the winding of the phase B of the motor, and as shown in fig. 3(B), the measurement current component i of the α axis in the α - β B coordinate system is_αbMeasuring current i from phase A_aAnd B-phase measuring current i_bObtained by Clark transformation and is represented as

Estimated current component of alpha axis in alpha-beta b coordinate systemEstimating the current i from the d-q axis in the control loop^* _dAnd i^* _qObtained by Park transformation and is represented as

Measuring current component i according to alpha axis under alpha-beta b coordinate system_αbAnd estimating the current componentCalculating the measured current component i_αbAnd estimating the current componentAbsolute value of residual error of epsilon_bIs shown as

And comparing the residual absolute value of the alpha-axis current in the alpha-beta a coordinate system and the residual absolute value of the alpha-axis current in the alpha-beta b coordinate system with a set residual threshold value to obtain a fault current sensor positioning result.

Specifically, the invention uses the residual absolute value epsilon of alpha-axis current in an alpha-beta a coordinate system_aAnd the residual absolute value epsilon of alpha-axis current under an alpha-beta b coordinate system_bComparing with a set residual threshold epsilon:

if the absolute value of the residual error is epsilon_aIf the current is less than the set residual error threshold epsilon, judging that the A-phase current sensor does not have a fault;

if the absolute value of the residual error is epsilon_aIf the current is greater than the set residual error threshold epsilon, judging that the A-phase current sensor has a fault;

if the absolute value of the residual error is epsilon_bIf the current is less than the set residual error threshold epsilon, judging that the B-phase current sensor does not have a fault;

if the absolute value of the residual error is epsilon_bAnd if the residual error is larger than the set residual error threshold epsilon, judging that the B-phase current sensor has a fault.

S3, sampling phase current values acquired by the fault current sensor, and constructing fault identification variables;

in the present embodiment, step S3 specifically includes the following substeps S3-1 to S3-5:

s3-1, sampling phase current values acquired by a fault current sensor to obtain phase current values of all sampling points in a phase current period;

s3-2, calculating the sum S of the phase current values of all sampling points according to the phase current values of all sampling points in one phase current period_xIs shown as

Wherein i_x(N) is the phase current value of the nth sampling point in one phase current period, and N is the number of sampling points in one phase current period;

s3-3, sampling after deriving the phase current value acquired by the fault current sensor to obtain phase current derivative values of all sampling points in a phase current period;

s3-4, calculating the sum d of phase current derivative values of any two continuous sampling points_x(n) is represented by

d_x(n)＝i′_x(n)+i′_x(n-1)

Wherein, i'_x(n) is the current derivative value at the n sampling point in one phase current cycle, where i'_x(n-1) is the current derivative value of the (n-1) th sampling point in one phase current period;

s3-5, calculating the sum S of the phase current values_xSum of derivative values of sum phase currents d_x(n) constructing fault recognition variables (S)_x，d_x(n))。

And S4, identifying the fault type of the current sensor according to the constructed fault identification variable.

In the present embodiment, step S4 specifically includes the following substeps S4-1 to S4-3:

s4-1, identifying variables from the constructed fault (S)_x，d_x(n)) determining the sum S of the phase current values at all sampling points within a phase current period_xWhether or not less than a set threshold S_th(ii) a If yes, go to step S4-2; otherwise, executing step S4-3;

s4-2, judging the sum d of phase current derivative values of any two continuous sampling points in one phase current period_x(n) is equal to zero; if yes, judging that the fault current sensor is a broken line fault; otherwise, judging the fault current sensor as a gain fault;

s4-3, judging the sum d of phase current derivative values of any two continuous sampling points in one phase current period_x(n) is equal to zero; if yes, judging the fault current sensor to be a stuck fault; otherwise, judging the fault current sensor to be a bias fault.

The method for identifying the fault type of the current sensor is verified through simulation, and an experimental result is given;

the motor runs at 600rpm, the motor is in a normal running state for 0-0.5s, the A-phase current sensor has a disconnection fault in 0.5s, and the motor is restored to run after 0.5 s; when the time is 1.5s, the A-phase current sensor has a stuck fault, and the operation is recovered after the same time is 0.5 s; when the time is 2.5s, the A-phase current sensor has a disconnection fault, and the operation is recovered after 0.5 s; at 3.5s, the A-phase current sensor has a disconnection fault, and the operation is recovered after 0.5s, wherein the waveform of the A-phase current is shown in FIG. 4 (a); the results of the diagnosis are shown in FIGS. 4(b) to 5 (e).

Experimental results prove that the method provided by the invention can realize the identification of the fault type of the current sensor.

The invention provides a method for positioning and identifying the fault of a current sensor of a permanent magnet motor driving system, which can also select other fault sensor positioning methods, such as: the fault diagnosis method based on the synovial observer is combined with the current sensor fault type identification method, and the fault location and identification of the current sensor can be still carried out.

In a permanent magnet motor drive system equipped with three current sensors, a suitable fault sensor positioning method can also be selected, such as: the fault current sensor is positioned by utilizing the full-order adaptive observer, and the fault positioning and identification of the current sensor can still be carried out by combining the fault type identification method of the current sensor.

Example 2

The invention also provides a device for identifying the fault type of the current sensor of the permanent magnet motor driving system, which comprises:

the data acquisition module is used for acquiring three-phase stator current signals of the permanent magnet motor and position signals of a permanent magnet motor rotor;

the fault positioning module is used for positioning the fault current sensor according to the collected three-phase stator current signals and the dq-axis reference current signals;

the diagnostic variable construction module is used for sampling phase current values acquired by the fault current sensor and constructing fault identification variables;

and the fault identification module is used for identifying the fault type of the current sensor according to the constructed fault identification variable.

The embodiment of the current sensor fault type identification device part of the permanent magnet motor driving system provided by the invention corresponds to the embodiment of the method part, and has the beneficial effect of the current sensor fault type identification method of the permanent magnet motor driving system. For this reason, please refer to the description of the method section for the embodiment of the apparatus section, which is not repeated here.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.