On-line monitoring and compensation of stator inter-turn short circuit faults in permanent magnet synchronous machines

Abstract

Methods and systems for online monitoring and compensation of inter-turn short circuit faults (ISF) in windings of electric machines, such as permanent magnet synchronous machines, are provided. A method for characterizing an ISF in a winding of an electric machine includes measuring phase voltages and phase currents, calculating sequence components of the electric machine based on the phase voltages and the phase currents, determining a ratio between a percentage of shorted turns in the winding and a fault loop resistance based on the sequence components of the electric machine, and estimating a characteristic of the inter-turn short circuit fault using an unscented Kalman filter. The characteristic includes at least one of a fault current, the percentage of shorted turns, or the fault loop resistance. A method for compensating an ISF in a winding of an electric machine includes compensating the fault current based on a compensation current estimated from the unscented Kalman filter.

Description

[0001] Cross-references to related applications

[0002] This PCT international patent application claims the benefit and priority of U.S. Provisional Patent Application Serial No. 63 / 106,583, filed on October 28, 2020, entitled “Online Monitoring OfStator Inter-Turn Short Circuit Fault In Permanent Magnet SynchronousMachines,” the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] This disclosure generally relates to the detection and characterization of inter-turn short-circuit faults in the windings of an electric motor. Background Technology

[0004] Permanent magnet synchronous motors (PMSMs) are widely used in electric vehicle (EV) applications due to their high efficiency, high power density, light weight, and compactness. Safety and reliability are critical considerations in motors. One type of fault known to affect PMSMs is the inter-turn short-circuit fault (ISF). ISF can induce high current values ​​in the short-circuited winding branch, subsequently heating the local area, which ultimately causes the fault to propagate throughout the winding, potentially even shutting down the entire system if appropriate action is not taken. Therefore, there is increasing attention being paid to ISF monitoring in PMSMs. Previous research has provided various methods for detecting ISF in PMSMs. Based on application-specific technologies, ISF diagnostic methods can be categorized into model-based methods, signal-based methods, and artificial intelligence (AI)-based methods.

[0005] In model-based approaches, state observers are typically designed to identify motor fault parameters based on an unbalanced three-phase variable model of the faulty PMSM. For example, a flux linkage observer can be used to obtain the short-circuit ratio. An extended state observer can be used to monitor the unbalanced back electromotive force (EMF) in the faulty machine. However, known model-based methods may fail to adequately account for the resistance in the short-circuit path and / or short-circuit current, which is crucial for preventing further damage to the faulty machine.

[0006] Signal analysis methods, such as Motor Current Characteristic Analysis (MCSA), can be used to identify ISFs by obtaining specific current harmonics via Fast Fourier Transform (FFT). This method is generally non-invasive and cost-effective because it uses only the stator current to detect ISFs in the machine. Therefore, many signal analysis methods are applied to ISF detection algorithms, such as wavelet analysis, Short-Time Fourier Transform (STFT), and Hilbert-Huang Transform. Traditional signal-based fault detection methods are often limited by their ability to distinguish ISFs from other types of faults that may also have similar effects in the current spectrum. Specifically, when analyzing stator current harmonics, the effects of inherent asymmetry and voltage imbalance are largely ignored. Therefore, current harmonic analysis is often insufficient to reliably detect the severity of ISFs.

[0007] AI-based technologies have been applied to fault diagnosis using artificial neural networks (ANNs), fuzzy logic systems, and expert systems. Such AI-based methods can not only detect and estimate the severity of faults but also pinpoint their location. However, AI-based methods are computationally expensive, and they may be difficult to implement in real-world applications.

[0008] In summary, existing ISF detection methods have performance limitations, which may include: 1) unreliable indicators of fault severity; 2) inability to distinguish ISF from other faults; and 3) difficulty in practical application.

[0009] Inter-turn short-circuit faults (ISFs) account for 30% to 40% of faults in permanent magnet synchronous motors (PMSMs). ISFs can induce high current values ​​in the short-circuited winding branch, subsequently heating the localized area. This can eventually cause the fault to propagate throughout the winding and, if appropriate action is not taken immediately, may even cause the entire system to shut down. Therefore, reliable online ISF monitoring methods are beneficial for providing real-time information about the fault and preventing the resulting damage. Summary of the Invention

[0010] According to one aspect of this disclosure, a method for characterizing inter-turn short-circuit faults in the windings of an electric motor includes: determining phase voltages and phase currents of the motor; calculating sequence components of the motor based on the phase voltages and phase currents; determining a ratio between the percentage of short-circuited turns in the windings and the fault loop resistance based on the sequence components of the motor; and estimating at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter, said at least one characteristic including at least one of the following: fault current in the inter-turn short-circuit fault, percentage of short-circuited turns, and fault loop resistance.

[0011] According to one aspect of this disclosure, a method for compensating for inter-turn short-circuit faults in a motor is provided. The method includes: determining a plurality of phase voltages based on a current command; applying the plurality of phase voltages via an inverter to corresponding windings of a plurality of windings of the motor, one of which has an inter-turn short-circuit fault; determining a phase current in each of the plurality of windings; calculating a sequence component of the motor based on the plurality of phase voltages and phase currents; determining a change in a fault factor based on the sequence component; determining whether the change in the fault factor is greater than a fault threshold; in response to determining that the change in the fault factor is greater than the fault threshold, estimating at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter, said at least one characteristic including a fault current in the inter-turn short-circuit fault; determining a compensation current based on the fault current in the inter-turn short-circuit fault; and adjusting a current command based on the compensation current to compensate for the fault current.

[0012] According to one aspect of this disclosure, a system for compensating for inter-turn short-circuit faults in a motor having multiple windings is provided. The system includes: an inverter configured to apply phase voltages to corresponding windings of the plurality of windings, one of the windings having an inter-turn short-circuit fault; and a controller configured to: determine the phase voltages based on a current command; determine the phase current in each of the plurality of windings; calculate a sequence component of the motor based on the phase voltages and phase currents; calculate a change in a fault factor based on the sequence component; determine whether the change in the fault factor is greater than a fault threshold; in response to determining that the change in the fault factor is greater than the fault threshold, estimate at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter, the at least one characteristic including a fault current in the inter-turn short-circuit fault; determine a compensation current based on the fault current in the inter-turn short-circuit fault; and adjust the current command based on the compensation current to compensate for the fault current. Attached Figure Description

[0013] Further details, features, and advantages of the design of the present invention will become apparent from the following description of exemplary embodiments with reference to the accompanying drawings.

[0014] Figure 1 A block diagram of a system according to one aspect of this disclosure is shown;

[0015] Figure 2 A schematic diagram of a stator winding with an inter-turn short-circuit fault according to the present disclosure is shown;

[0016] Figure 3 This is a block diagram of a drive system for characterizing and compensating for inter-turn short-circuit faults (ISF) in an electric motor, based on various aspects of this disclosure.

[0017] Figure 4 This is a flowchart outlining the steps in a method for characterizing and compensating for ISF in an electric motor, based on various aspects of this disclosure;

[0018] Figure 5 It is a graph showing the estimated and actual ratio of short-circuit turns according to various aspects of this disclosure;

[0019] Figure 6 It is a diagram showing the estimated and actual fault resistance according to various aspects of this disclosure;

[0020] Figure 7 It is a diagram showing the estimated and actual fault currents according to various aspects of this disclosure;

[0021] Figure 8 The diagram illustrates the output torque of the PMSM under three different operating conditions according to various aspects of this disclosure: without ISF (time = 2s to 3s); with ISF but without feedforward compensation current (time = 3s to 4s); with ISF and with feedforward compensation current (time = 4s to 5s).

[0022] Figure 9 This is a bar graph listing the Fast Fourier Transform (FFT) analysis results of the PMSM output torque under ISF without compensation current according to various aspects of this disclosure; and

[0023] Figure 10 This is a bar graph listing the Fast Fourier Transform (FFT) analysis results of the PMSM output torque under ISF with compensated current according to various aspects of this disclosure. Detailed Implementation

[0024] Referring to the accompanying drawings (in which the same reference numerals indicate corresponding parts throughout the views), systems and methods for characterizing inter-turn short-circuit faults in motors are disclosed. More specifically, this disclosure describes a method as an example of an online monitoring method for inter-turn short circuits in permanent magnet synchronous motors (PMSMs). The term "online" can mean the motor is in place, or the electronic and / or mechanical hardware of the motor connected to its operating environment. For example, the methods and systems of this disclosure can be used to diagnose faults in PMSMs installed in electric vehicles (EVs). In some cases, the method can be performed as part of periodic maintenance or system checks. For example, an electric vehicle can perform the methods of this disclosure as part of a startup check to begin a driving session. In some embodiments, the method can be performed using hardware components already in place for operating the motor (e.g., motor drivers and controllers).

[0025] Figure 1A block diagram of a system 10 according to one aspect of this disclosure is shown. System 10 includes a motor driver 20 having one or more switching devices 22, such as field-effect transistors (FETs), configured to generate AC power on a set of motor leads 24 and / or rectify AC power from the motor leads 24. The motor leads 24 transmit power between the motor driver 20 and a motor 26. In the example system 10, the motor 26 is a permanent magnet synchronous motor (PMSM). However, system 10 can be used with other types of motors, such as wound field machines, inductive motors, and / or reluctance motors. The motor 26 is shown as a three-phase motor; however, the motor can have any number of phases. For example, the motor 26 can be a single-phase motor, a three-phase motor, or a higher-order multiphase motor. The motor 26 can be used as a motor, a generator, or a motor / generator that functions as both a motor and a generator. The motor driver 20 also includes a sensor 28, such as a voltage and current sensor, which can be configured to measure the voltage on or between the motor leads 24 and / or measure the current on the motor leads 24.

[0026] Figure 1 System 10 also includes a controller 30 that functionally communicates with motor driver 20. The controller 30 can be configured to control the operation of motor driver 20 and / or monitor parameters measured by sensor 28. The controller 30 includes a processor 32 coupled to memory 34. Memory 34 stores instructions, such as program code executed by processor 32. Memory 34 also includes a data memory 38 for storing data to be used by processor 32. For example, data memory 38 may record values ​​of parameters measured by sensor 28 and / or results of functions calculated by processor 32.

[0027] Figure 2 A schematic diagram 100 is shown of stator windings 102, 104, and 106 with inter-turn short-circuit faults according to this disclosure. Stator windings 102, 104, and 106 may be located within motor 26. Specifically, stator windings 102, 104, and 106 include phase A winding 102 with inter-turn short-circuit faults.

[0028] Figure 3 A block diagram of a drive system 200 for characterizing and compensating for inter-turn short-circuit faults (ISF) in motor 26 is shown. The drive system 200 includes a speed / torque controller 202 configured to generate current commands. To meet speed command Or torque command One of them. In some implementations, such as Figure 3 As shown, current command Includes d-axis current command and q-axis current command

[0029] The drive system 200 also includes a current regulator 204 configured to operate based on current commands. To generate d-axis and q-axis voltage commands u d u q To adjust the motor current i supplied to motor 26 a,b,c The current regulator 204 will control the d-axis current. q-axis current command And representing the motor current i supplied to motor 26 a,b,c The d-axis and q-axis motor current i d i q As input, the drive system 200 also includes a first converter block 206, which is configured to operate based on d-axis and q-axis voltage commands. d u q To generate phase voltage u a u b u c .

[0030] The drive system 200 also includes a pulse width modulator (PWM) 208, which is configured to generate a pulse width modulator (PWM) corresponding to the phase voltage u. a u b u c Each of these is represented by a PWM signal 209. The drive system 200 also includes an inverter 210 configured to switch DC power from the DC source 212 based on the PWM signal 209, so that the motor leads 211 connected to the motor 26 are energized with a corresponding phase voltage u. a u b u c .

[0031] The drive system 200 also includes one or more current sensors 214, which are configured to measure the phase current i in each of the corresponding motor leads 211. a i b i c The drive system 200 also includes a speed and position sensor 216 functionally coupled to the motor 26, which is configured to measure the motor speed ω. e and motor position θ e The drive system 200 also includes a second converter block 218, which is configured to be based on the phase current i a i b ic and motor position θ e To calculate the motor current i of the d-axis and q-axis d i q .

[0032] Figure 3 The drive system 200 also includes an ISF compensator 220, which is configured to compensate for inter-turn short-circuit faults (ISF) in one of the windings 102, 104, and 106 of the motor 26. One of the windings 102, 104, and 106 with an ISF can be referred to as the faulty winding. The ISF compensator 220 includes a third converter block 222, which is configured to compensate for phase current i a i b i c To calculate the αβ domain current signal i α i β And based on the phase voltage u applied to motor 26 a u b u c To calculate the voltage signal u in the αβ domain α u β . Figure 3 The drive system 200 also includes an unscented Kalman filter (UKF) block 224, which is configured to estimate fault parameters μ. This includes the ratio (μ) of short-circuited turns to total turns in the faulty winding of motor 26 and the estimated fault current in the faulty winding of motor 26. UKF block 224 can convert the αβ domain current signal i from the third transform block 222. α ,、i β and αβ domain voltage signal u α u β As input, UKF block 224 can also input the motor speed ω from speed and position sensor 216. e and motor position θ e The signal is used as input.

[0033] The ISF compensator 220 of the drive system 200 also includes a sequence analyzer block 226, which is configured to determine the estimated fault resistance r of the short-circuited turns in the faulty winding of the motor 26. f The ISF compensator 220 of the drive system 200 also includes a compensation current calculator block 228, which is configured to calculate the q-axis compensation current i for compensating for the effects of a faulty winding of the motor 26. q com and d-axis compensation current i d com .

[0034] The ISF compensator 220 of the drive system 200 also includes a q-axis current adder 230, which is configured to add q-axis current commands. With q-axis compensation current i q com Add them together to calculate the modified q-axis current command i′. q The ISF compensator 220 of the drive system 200 also includes a d-axis current adder 232, which is configured to convert the 2-axis current command... With d-axis compensation current i d com Add them together to calculate the modified d-axis current command i′. d The current regulator 204 can modify these current commands i′ d 、i′ q As input, it is used to control the current supplied to motor 26.

[0035] According to one aspect of this disclosure, a method for characterizing inter-turn short-circuit faults (ISF) in an electric motor is provided. The proposed method includes: detecting characteristics of the motor, which can be performed while the motor is running; determining, based on these characteristics, whether an inter-turn short-circuit fault exists on one or more windings of the motor; and determining the severity of characteristics associated with the ISF, which can be used as an indicator of the motor's operating condition.

[0036] According to one aspect of this disclosure, a method 300 for characterizing inter-turn short-circuit faults in the windings of an electric motor is provided. This method 300 can be summarized in Algorithm I, which is listed below.

[0037]

[0038] A method 300 for characterizing inter-turn short-circuit faults in the windings of an electric motor is provided and is also provided. Figure 4 The flowchart illustrates this. All or part of this method 300 can be executed by the drive system 200.

[0039] Method 300 includes measuring phase voltage and phase current at step 302. For example, phase voltage and phase current can be measured by sensors within a motor driver configured to supply AC power to the motor.

[0040] Method 300 further includes calculating the sequence component of the motor at step 304. This sequence component may include, for example, the positive sequence impedance Z. pp The positive sequence impedance Z pp It can be calculated as Z pp =R+jω e L, where R is the phase resistance, L is the phase inductance, and ω eIt is the electrical angular velocity of the rotor. Step 304 can be executed by processor 32 executing instructions to implement UKF block 224 and / or sequence analyzer block 226.

[0041] Method 300 further includes determining the change in the failure factor (ΔFF) based on the order component at step 306. In some embodiments, step 306 may include calculating the failure factor FF, which can be done using an equation. To calculate, where It is positive sequence current. It is the positive sequence voltage, and Z pp It is a positive sequence impedance. Step 306 then allows monitoring of the change in the fault factor FF (i.e., ΔFF) to detect the ISF. If there is no ISF, ΔFF will be zero even with voltage imbalance and inherent asymmetry in the motor. If there is an ISF, ΔFF will no longer be zero.

[0042] Step 306 can be performed by the processor 32 executing instructions to determine the change ΔFF of the fault factor, or otherwise determining the change ΔFF of the fault factor. For example, the change ΔFF of the fault factor can be determined by tracking the fault factor FF and calculating the change as ΔFF = FF(k) - FF(k-1). FF(k) is the value of the fault factor FF at the current time, and FF(k-1) is the value of FF at a previous time. More complex tracking may be involved to determine the change ΔFF of the fault factor based on the value of the fault factor FF over a longer time period.

[0043] The change in the fault factor ΔFF can be expressed as Where ΔFF is the change in the fault factor, FF h It is a fault factor for well-functioning windings, FF f It is the fault factor of the faulty winding, Z pf It is the sequence impedance of the fault winding with positive sequence current, Z pp It is the sequence impedance of the positive sequence current, μ is the ratio of the short-circuited turns to the total turns of a winding with an inter-turn short-circuit fault, and... It is the fault current. From the equation It can be seen that the change in the fault factor (ΔFF) is only related to the ISF and is not affected by the motor's voltage imbalance or inherent asymmetry. When the motor does not have an ISF, the fault factor (i.e., FF) h This can be determined using equation (a):

[0044]

[0045] When the motor has an ISF (Independent Fault Factor), the fault factor (i.e., FF) fThis can be expressed using equation (b):

[0046]

[0047] The change in FF (ΔFF) when ISF occurs can be expressed by equation (c):

[0048]

[0049] It can be used To calculate the failure factor FF h FF f Equations (a) and (b) above can be used only for the derivation of equation (c). If the motor does not have an ISF, then ΔFF will be zero even with voltage imbalance and inherent asymmetry. If an ISF exists, ΔFF will have a non-zero value, and ΔFF will increase with the severity of the fault. Therefore, even with voltage imbalance and inherent asymmetry in the motor, tracking ΔFF can detect the ISF.

[0050] Method 300 further includes determining at step 308 whether the change in the fault factor is greater than a fault threshold. Step 304 can be performed by executing instructions via processor 32 to perform a comparison. The fault threshold may be predetermined. Alternatively, the fault threshold may be adjusted during system operation.

[0051] Method 300 further includes determining, at step 310, the percentage of short-circuited turns in the winding and the fault loop resistance r based on the sequence component of the motor. f The ratio between them. The percentage of short-circuited turns in the winding can be directly related to the ratio μ of short-circuited turns to total turns in a winding with ISF. In some implementations, step 310 may include using the equation: in Step 310 can execute instructions via processor 32 to determine the percentage of short-circuited turns in the winding (or the ratio of short-circuited turns to total turns in the winding (μ)) and the fault loop resistance r. f The ratio between the two can be used to execute the procedure. Step 310 can be executed in response to determining at step 308 that the change in the fault factor is greater than the fault threshold.

[0052] Method 300 further includes estimating the characteristics of the inter-turn short-circuit fault (ISF) at step 312 using an unscented Kalman filter. The ISF characteristics may include one or more of the following: fault current. Fault resistance (r) fAnd / or the ratio (μ) of short-circuited turns to total turns in the winding. In some embodiments, step 312 may include processor 32 executing instructions to implement unscented Kalman filter (UKF) block 224 to estimate the ratio μ of short-circuited turns to total turns in the faulty winding of the motor and / or the fault current. Step 312 may include processor 32 executing instructions to implement sequence analyzer block 226 to determine the fault resistance r of the short-circuited turn in the faulty winding of the motor. f Step 312 can be executed in response to determining at step 308 that the change in the fault factor is greater than the fault threshold.

[0053] Method 300 further includes determining the absolute value of the fault current at step 314. Is it less than the fault threshold? This fault threshold can also be referred to as "..." The fault threshold. Step 314 may include processor 32 executing instructions to calculate the absolute value of the fault current. And the absolute value of the fault current The comparison is made with a fault threshold. The fault threshold can be predetermined. Alternatively, the fault threshold can be adjusted during system operation.

[0054] Method 300 further includes, at step 316, responding to determining that the absolute value of the fault current is less than a fault threshold, based on an estimate from the UKF. To compensate for fault current. Step 316 can be implemented using ISF compensator 220. For example, step 316 may include processor 32 implementing some or all of ISF compensator 220.

[0055] Method 300 further includes, at step 318, a response to determining the absolute value of the fault current. The motor is stopped and / or marked as faulty if the fault threshold is not lowered. Marking the motor as faulty designates it as requiring maintenance. For example, processor 32 may generate and store a diagnostic fault code (DTC) that designates the motor as requiring maintenance. Alternatively or additionally, processor 32 may transmit one or more pieces of information or otherwise indicate the condition of the motor and / or mark it as faulty. For example, processor 32 may cause a warning light to illuminate and / or display a warning message on the user interface.

[0056] A mathematical model of the PMSM (Pulse-Circuit Severity Filter) is proposed to understand the behavior of machines with inter-turn faults. Then, by analyzing the sequence components, the relationship between the percentage of short-circuited turns and the fault loop resistance is derived. An unscented Kalman filter (UKF) is employed to estimate the fault current, the percentage of short-circuited turns, and the fault loop resistance in the PMSM. In the proposed method, the effects of voltage imbalance and inherent asymmetry are considered and eliminated during fault severity estimation.

[0057] Stator faults account for approximately 30% of all faults in industrial motors. According to one aspect of this disclosure, a method based on unscented Kalman filtering (UKF) is proposed for estimating the severity level of stator inter-turn short-circuit faults in permanent magnet synchronous motors (PMSMs).

[0058] A mathematical model of the PMSM is described. This model helps describe the behavior of a machine with inter-turn faults, where the effects of machine asymmetry and voltage imbalance are considered. The UKF (Universal Key Factor) is then used to estimate fault variables in the PMSM, such as short-circuit current, percentage of short-circuit turns, and fault loop resistance, to monitor fault severity. To validate the proposed method, system simulations based on finite element analysis (FEA) are performed, considering various fault severity levels under different load and voltage imbalance conditions.

[0059] PMSM modeling with ISF faults

[0060] When an intermittent fault (ISF) occurs, the effective number of turns in the motor windings decreases. This phenomenon leads to an imbalance in the armature current of the machine and degrades its performance. ISF is typically caused by an additional fault resistor R. f To model, its in Figure 2 The winding shown is for phase A. Here, it is assumed that the well-functioning winding in phase A is winding a. s1 And the faulty part is winding a. s2 Assume N is the number of turns in phase A, and the number of short-circuited turns is N. s μ=N s / N represents the ratio of short-circuit turns to total turns in the winding.

[0061] ISF model in abc coordinates

[0062] The motor model under fault conditions can be written in the abc coordinate system as shown in the following equation (1), which also includes the fault components caused in the motor phase.

[0063]

[0064] e f =μe a

[0065] Ra2=(1-μ)R

[0066] L a2 =(1-μ) 2 L

[0067] M a1a2 =μ(1-μ)M (2)

[0068] Among them, V a V b Vc i a i b i c and e a e b e c These represent the phase voltage, current, and reverse EMF of phases a, b, and c, respectively; R, L, and M represent the stator phase resistance, self-inductance, and mutual inductance of a well-functioning machine, respectively; R a2 and L a2 M represents the resistance and self-inductance of the faulty winding as2. a1a2 M a2b and M a2c a s2 With winding a s1 b s and c s Mutual intuition between them; I f r f and e f These are the fault current, fault resistance, and fault reverse EMF, respectively.

[0069] The electromagnetic torque generated under ISF can be expressed as:

[0070]

[0071] Where T e It is electromagnetic torque, and ω m It's the rotational speed.

[0072] ISF model in αβ coordinates

[0073] For a machine with one slot per pole and one phase, M a2b It can be considered equal to M a2c By using the Clarke transform, (1) can be rewritten as follows:

[0074]

[0075]

[0076] L' = LM

[0077]

[0078] Ordinal component analysis in PMSM

[0079] The positive-sequence and negative-sequence voltages of the PMSM under inter-turn faults in the stator winding can be expressed as follows:

[0080]

[0081]

[0082] in, and These are the positive sequence current, negative sequence current, and the current in the fault circuit section, respectively. and These are positive-order inverse EMF and negative-order inverse EMF, respectively; Z pp and Z nn These are the positive-sequence impedance and the negative-sequence impedance, respectively; Z pn and Z np It is a non-diagonal sequence impedance / cross sequence impedance, which exhibits an inherent asymmetry effect; Z pf and Z nf These are the impedances corresponding to the effects of faults in the positive-sequence and negative-sequence models, respectively.

[0083] Using a PMSM steady-state model with ISF, the order component model of PMSM can be expressed as:

[0084] Z pp =Z nn =R+jω e L

[0085]

[0086]

[0087]

[0088]

[0089] Where ω e It is the excitation frequency.

[0090] Fault Factor Then we have:

[0091]

[0092] Here, the subscripts h and f indicate a working machine and a faulty machine, respectively.

[0093] Substituting equation (8) into equation (7), the difference between a well-functioning motor and a faulty motor can be expressed as equation (9).

[0094]

[0095] Therefore, when a fault occurs, ΔFF has a fault-related value. Under good operating conditions, Z pn It should be zero. Therefore, by tracking changes in ΔFF, ISF can be detected even under conditions of motor voltage imbalance and inherent asymmetry. Furthermore, by monitoring the fault factor FF, the relationship between μ and... The relationship between these factors is as follows: The change in the fault factor ΔFF can be used as an indicator of the Independent Fault Factor (ISF), which can be compared with the fault threshold to determine whether the motor has an ISF. If there is no ISF, ΔFF will be zero even with voltage imbalance and inherent asymmetry in the motor. If there is an ISF, ΔFF will not be zero, and the change in the fault factor ΔFF increases with the severity of the fault.

[0096] During the initial fault detection phase, μ is small, r f Larger. Furthermore... and Compared to this, it can be ignored. Therefore, according to equation (7), r can be... f The relationship between μ and μ is calculated as follows (10).

[0097]

[0098] As long as three parameters are estimated ( r f One of the parameters is μ, and the other two parameters can be easily calculated using (9) and (10). The estimation process is presented in the next section.

[0099] Unscented Kalman Filter for Estimating Fault Parameters

[0100] Unscented Kalman filtering (UKF) omits the computation of covariance and the linearization process of the estimate. Discrete-time nonlinear dynamic systems can be represented as...

[0101]

[0102] Where, x k It is the unobserved state of the system; y k These are observed measurements; u k It is a known external input; w k and v k These are zero-mean Gaussian white noise with covariances Q and R, respectively; Q and R are the noise covariances of the process and measurement, respectively; and f(,) and h(,) represent nonlinear functions with continuous first-order partial derivatives.

[0103] The UKF algorithm generally consists of four steps (initialization, unscented transformation, prediction, and correction). First, the average value of the initial state... Covariance P of the initial state x As set in (12). Then, an unscented transformation is used to select samples with predetermined weights W around the mean. i A set of sigma points. The output will be estimated by processing each sigma point using f(,) and h(,). In obtaining Then, the output error covariance P can be calculated. y and cross covariance P xy Finally, and P x Updated to and P x The detailed UKF estimation method is shown below.

[0104] i. Initial value

[0105]

[0106] Where x0 is the initial value of the state.

[0107] ii. Unscented transformation

[0108]

[0109]

[0110] Where n is The dimension; λ is the design parameter in the UKF algorithm, which is called the scaling parameter.

[0111] iii Prediction

[0112]

[0113]

[0114]

[0115] iv. Correction

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] To establish a state-space model of a PMSM with ISF, we define equation (23):

[0122]

[0123] And the state vector x = [x1 x2 x3] T The state-space model of inter-turn short-circuit faults in PMSM is represented by the following equation (24):

[0124]

[0125] Torque ripple compensation under ISF

[0126] Assumption Among them I f is i f The amplitude, ω e It is the electric angular velocity of the rotor. It is the initial phase angle of the short-circuit current. The electromagnetic torque generated in the dq axis under ISF can be expressed by the following equation (25).

[0127]

[0128] in It is a permanent magnet flux linkage. As can be seen from equation (25), when the fault current is not zero, there is a second harmonic in the torque equation, which will cause torque pulsation.

[0129] To eliminate torque ripple caused by ISF, the fault current μi estimated from UKF is used. f The current will be applied to phase A. Using current compensation, the torque equation in (2) will be updated to the following equation (26).

[0130]

[0131] As can be seen from equation (26), after compensation, there are no longer fault terms in the torque equation. This is achieved by using the Parker transformation T... abc_dq The compensation current on the dq axis can be expressed as the following equation (27).

[0132]

[0133] Where θ e It is the electrical angle of the rotor.

[0134] Transformation T used in transform blocks 222, 218, and 206 abc_αβ T abc_dq and T dq_abc The matrices are defined by the following equations (28), (29) and (30):

[0135]

[0136]

[0137]

[0138] Verification in FEA-based system simulation

[0139] Simulation results in Figures 5 to 7 As shown in the figure, Figure 5 This is a graph comparing the estimated ratio (μ) of short-circuited turns to total turns in the faulty winding with the actual ratio (μ). Specifically, Figure 3 The first curve 420 includes the estimated μ, which is estimated using the methods of this disclosure. Figure 5 It also includes the second curve of the actual μ, Figure 422. Figure 6 This shows the estimated fault resistance (r) in the faulty winding. f ) and the actual fault resistance (r f The diagram. Specifically, Figure 6 Including the estimated fault resistance r f The third curve, 430, shows the estimated fault resistance r. f The methods described in this disclosure are used for estimation. Figure 6 It also includes the actual fault resistance r f The fourth curve is shown in Figure 432. Figure 7 This shows the estimated fault current (I) in the fault winding. f ) and the actual fault current (I f A comparison diagram between ) . Specifically, Figure 7 Including the estimated fault current I f The fifth curve, 440, shows the estimated fault current I. f The methods described in this disclosure are used for estimation. Figure 7 It also includes the actual fault current I f The sixth curve is shown in Figure 442.

[0140] Figure 8 The seventh curve 450 shows the output torque of the PMSM 26 under three different operating conditions. Condition 452, without ISF, extends from time = 2s to 3s. Condition 454, with ISF but without feedforward compensation current, extends from time = 3s to 4s. Condition 456, with ISF and feedforward compensation current, extends from time = 4s to 5s.

[0141] Figure 9 A bar graph showing the Fast Fourier Transform (FFT) analysis results of the PMSM output torque under ISF without compensation current is displayed. Figure 9 The bar graph shows the torque at approximately 10 Nm for the 0th harmonic and at approximately 0.5 Nm for the 2nd harmonic. Figure 10 This is a bar graph showing the Fast Fourier Transform (FFT) analysis results of the PMSM output torque under ISF with compensation current. Figure 10 The bar graph shows the torque at approximately 10 Nm for the 0th harmonic and at approximately 0.05 Nm for the 2nd harmonic.

[0142] According to one aspect of this disclosure, the sequence components of the motor are calculated by measuring the three-phase voltage and current. If the ISF index composed of the sequence components reaches the fault threshold, the relationship between the percentage of short-circuited turns and the fault loop resistance is determined by comparing the sequence components with those of a well-functioning motor, and the fault parameters, including the fault current in the faulty winding of the motor, the percentage of short-circuited turns, and the fault loop resistance, are estimated using the UKF.

[0143] According to one aspect of this disclosure, the relationship between the percentage of short-circuited turns and the fault loop resistance is derived by analyzing the sequence components of a motor such as a PMSM. Then, an unscented Kalman filter (UKF) is employed to estimate the fault current, the percentage of short-circuited turns, and the fault loop resistance in the faulted winding of the motor. During fault severity estimation, the effects of voltage imbalance and inherent asymmetry are considered and eliminated in the proposed method. No complex AI-based algorithms are involved throughout the estimation process.

[0144] According to one aspect of this disclosure, a compensation current for inter-turn short-circuit faults is estimated from an unscented Kalman filter (UKF) to eliminate torque ripples caused by inter-turn short-circuit faults.

[0145] According to one aspect of this disclosure, the relationship between the percentage of short-circuited turns and the fault loop resistance is derived by analyzing the sequence components of a motor such as a PMSM. Then, an unscented Kalman filter (UKF) is employed to estimate the fault current, the percentage of short-circuited turns, and the fault loop resistance in the faulted winding of the motor. During fault severity estimation, the effects of voltage imbalance and inherent asymmetry are considered and eliminated in the proposed method. No complex AI-based algorithms are involved throughout the estimation process.

[0146] A method is provided for characterizing inter-turn short-circuit faults in the windings of an electric motor. The method includes: determining phase voltages and phase currents of the motor; calculating sequence components of the motor based on the phase voltages and phase currents; determining a ratio between the percentage of short-circuited turns in the windings and the fault loop resistance based on the sequence components of the motor; and estimating at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter, said at least one characteristic including at least one of: fault current, percentage of short-circuited turns, and fault loop resistance.

[0147] In some implementations, at least one characteristic of an inter-turn short-circuit fault includes the fault current, the percentage of short-circuited turns, and the fault loop resistance.

[0148] In some implementations, the motor is a permanent magnet synchronous motor.

[0149] A method for compensating for inter-turn short-circuit faults in a motor includes: determining multiple phase voltages based on a current command; applying the multiple phase voltages via an inverter to corresponding windings of multiple windings of the motor, one of which has an inter-turn short-circuit fault; determining a phase current in each of the multiple windings; calculating a sequence component of the motor based on the multiple phase voltages and phase currents; determining a change in a fault factor based on the sequence component; determining whether the change in the fault factor is greater than a fault threshold; estimating at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter in response to determining that the change in the fault factor is greater than the fault threshold, the at least one characteristic including a fault current in the inter-turn short-circuit fault; determining a compensation current based on the fault current in the inter-turn short-circuit fault; and adjusting a current command based on the compensation current to compensate for the fault current.

[0150] In some implementations, at least one characteristic of the inter-turn short-circuit fault also includes fault resistance.

[0151] In some implementations, at least one characteristic of the inter-turn short-circuit fault also includes the ratio of short-circuit turns to total turns in a winding with an inter-turn short-circuit fault.

[0152] In some implementations, determining the compensation current based on the fault current in an inter-turn short-circuit fault also includes calculating the compensation current based on the ratio of short-circuit turns to total turns in a winding with an inter-turn short-circuit fault.

[0153] In some implementations, the method further includes: determining the absolute value of the fault current; determining whether the absolute value of the fault current is less than a fault threshold; and wherein a current adjustment command based on a compensation current is executed to compensate for the fault current only if the absolute value of the fault current is less than the fault threshold.

[0154] In some implementations, the method further includes: determining the absolute value of the fault current; determining whether the absolute value of the fault current is greater than a fault threshold; and marking the motor as faulty in response to determining that the absolute value of the fault current is greater than the fault threshold.

[0155] In some implementations, the method further includes stopping the motor in response to determining that the absolute value of the fault current is greater than a fault threshold.

[0156] In some implementations, determining the change in the fault factor based on the order component includes calculating the fault factor (FF) as... in It is positive sequence current. It is the positive sequence voltage, and Z pp It is a positive sequence impedance.

[0157] In some implementations, the motor is a permanent magnet synchronous motor.

[0158] A system is provided for compensating for inter-turn short-circuit faults in a motor having multiple windings. The system includes: an inverter configured to apply phase voltages to corresponding windings of the plurality of windings, one of which has an inter-turn short-circuit fault; and a controller. The controller is configured to: determine the phase voltages based on current commands; determine the phase currents in each of the plurality of windings; calculate a sequence component of the motor based on the phase voltages and phase currents; calculate a change in a fault factor based on the sequence components; determine whether the change in the fault factor is greater than a fault threshold; in response to determining that the change in the fault factor is greater than the fault threshold, estimate at least one characteristic of the inter-turn short-circuit fault using an unscented Kalman filter, the at least one characteristic including a fault current in the inter-turn short-circuit fault; determine a compensation current based on the fault current in the inter-turn short-circuit fault; and adjust the current commands based on the compensation current to compensate for the fault current.

[0159] In some implementations, at least one characteristic of the inter-turn short-circuit fault also includes the fault resistance and the ratio of short-circuit turns to total turns in one of the multiple windings having the inter-turn short-circuit fault.

[0160] In some implementations, determining the compensation current based on the fault current in an inter-turn short-circuit fault also includes calculating the compensation current based on the ratio of short-circuit turns to total turns in a winding with an inter-turn short-circuit fault.

[0161] The aforementioned controller and its associated methods and / or processes, as well as their steps, may be implemented in hardware, software, or any combination of hardware and software suitable for a particular application. Hardware may include general-purpose computers and / or special-purpose computing devices, or specific aspects or components of a particular computing device. Processes may be implemented in one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors, or other programmable devices, as well as internal and / or external memory. Processes may also be implemented, or alternatively, in application-specific integrated circuits, programmable gate arrays, programmable array logic, or any other means or combination of means that can be configured to process electronic signals. It will also be appreciated that one or more of the processes may be implemented as computer-executable code capable of executing on a machine-readable medium.

[0162] Computer executable code can be created using a structured programming language such as C, an object-oriented programming language such as C++, or any other high- or low-level programming language (including assembly language, hardware description language, and database programming language and techniques). The computer executable code can be stored, compiled, or interpreted to run on one of the above-described devices and processor architectures, or different combinations of hardware and software, or any other machine capable of executing program instructions.

[0163] Therefore, in one aspect, each of the methods described above and combinations thereof can be implemented in computer-executable code that performs its steps when executed on one or more computing devices. In another aspect, the methods can be implemented in a system that performs its steps and can be distributed among devices in various ways, or all functionality can be integrated into a dedicated, separate device or other hardware. In yet another aspect, the means for performing the steps associated with the processes described above can include any of the aforementioned hardware and / or software. All such permutations and combinations are intended to fall within the scope of this disclosure.

[0164] The foregoing description is not intended to be exhaustive or limiting of this disclosure. Elements or features of a particular embodiment are generally not limited to that particular embodiment, but are interchangeable and can be used in chosen embodiments where applicable, even if not specifically shown or described. Embodiments can also vary in many ways. Such variations should not be considered a departure from this disclosure, and all such modifications are intended to be included within the scope of this disclosure.

Claims

1. A method for compensating for inter-turn short-circuit faults in an electric motor, the method comprising: Multiple phase voltages are determined based on voltage commands generated from current commands; The multiple phase voltages are applied to corresponding windings of multiple windings of the motor via an inverter, one of the windings having the inter-turn short-circuit fault; Determine the phase current in each of the plurality of windings; The sequence component of the motor is calculated based on the multiple phase voltages and the phase currents; monitoring a change of a fault factor FF calculated as wherein is the positive sequence current, is the positive sequence voltage, and is the positive sequence impedance; If the change in the fault factor is determined, determine whether the change in the fault factor is greater than the fault threshold. In response to determining that the change in the fault factor is greater than the fault threshold, an unscented Kalman filter is used to estimate at least one characteristic of the inter-turn short-circuit fault, the at least one characteristic including the fault current in the inter-turn short-circuit fault; The compensation current is determined based on the fault current in the inter-turn short-circuit fault. as well as The current command is adjusted based on the compensation current to compensate for the fault current.

2. The method of claim 1, wherein, At least one characteristic of the inter-turn short-circuit fault also includes fault resistance.

3. The method of claim 1, wherein, At least one characteristic of the inter-turn short-circuit fault also includes the ratio of short-circuit turns to total turns in the winding having the inter-turn short-circuit fault.

4. The method of claim 1, wherein, Determining the compensation current based on the fault current in the inter-turn short-circuit fault also includes calculating the compensation current based on the product of the ratio of the short-circuit turns to the total turns in the winding with the inter-turn short-circuit fault and the fault current.

5. The method according to claim 1, further comprising: Determine the absolute value of the fault current; Determine whether the absolute value of the fault current is less than the fault threshold; as well as Specifically, the current adjustment command based on the compensation current is executed to compensate for the fault current only if the absolute value of the fault current is less than the fault threshold.

6. The method according to claim 1, further comprising: Determine the absolute value of the fault current; Determine whether the absolute value of the fault current is greater than the fault threshold; as well as The motor is marked as faulty in response to determining that the absolute value of the fault current is greater than the fault threshold.

7. The method of claim 5, further comprising: The motor is stopped in response to determining that the absolute value of the fault current is greater than the fault threshold.

8. The method of claim 1, wherein, The motor is a permanent magnet synchronous motor.

9. A system for compensating for inter-turn short-circuit faults in a motor having multiple windings, comprising: An inverter configured to apply a phase voltage to a corresponding winding of the plurality of windings, one of the plurality of windings having the inter-turn short-circuit fault; as well as The controller is configured to: The phase voltage is determined based on the voltage command generated according to the current command; Determine the phase current in each of the plurality of windings; The sequence component of the motor is calculated based on the phase voltage and the phase current; Monitoring a change in a fault factor FF calculated as wherein is the positive sequence current, is the positive sequence voltage, and is the positive sequence impedance; If the change in the fault factor is determined, determine whether the change in the fault factor is greater than the fault threshold. In response to determining that the change in the fault factor is greater than the fault threshold, an unscented Kalman filter is used to estimate at least one characteristic of the inter-turn short-circuit fault, the at least one characteristic including the fault current in the inter-turn short-circuit fault. The compensation current is determined based on the fault current in the inter-turn short-circuit fault. as well as The current command is adjusted based on the compensation current to compensate for the fault current.

10. The system of claim 9, wherein, At least one characteristic of the inter-turn short-circuit fault also includes the fault resistance and the ratio of short-circuit turns to total turns in one of the plurality of windings having the inter-turn short-circuit fault.

11. The system according to claim 9, wherein, Determining the compensation current based on the fault current in the inter-turn short-circuit fault also includes calculating the compensation current based on the product of the ratio of the short-circuit turns to the total turns in the winding with the inter-turn short-circuit fault and the fault current.

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