Converter sub-module IGBT open-circuit fault rapid diagnosis and positioning method

Abstract

The application discloses a converter submodule IGBT open-circuit fault rapid diagnosis and positioning method, each phase of a three-phase converter is composed of upper and lower bridge arms, six bridge arms are shared by the three phases, and each bridge arm is composed of a plurality of series-connected submodules and an inductor in series; the method comprises: fault diagnosis and fault positioning; the fault diagnosis is to determine whether a submodule open-circuit fault occurs by optimally estimating three-phase ring currents and output currents through an adaptive extended Kalman filtering algorithm, and to identify the fault position of the bridge arm in the fault phase; the fault positioning is to group and reconstruct the submodules in the fault bridge arm through the fault bridge arm corresponding to the fault position of the bridge arm, to form a reconstructed subunit, and then to optimally estimate the voltage of the reconstructed subunit by using the adaptive extended Kalman filtering algorithm, and to realize positioning of the fault submodule according to the residual error of the voltage of the reconstructed subunit. The problems of a large number of state observers and long diagnosis time when the number of submodules is large are avoided.

Description

Technical Field

[0001] This invention belongs to the field of power electronics technology, specifically relating to a method for rapid diagnosis and location of open-circuit faults in IGBTs of converter submodules. Background Technology

[0002] Since its introduction by German scholar Rainer Marquardt in 2001, the Modular Multilevel Converter (MMC) topology has been highly successful. Because each bridge arm connects multiple identical power units or submodules in series, eliminating the need for phase-shifting transformers and simplifying the topology, MMC offers numerous advantages over traditional multilevel converters, including excellent scalability, a simpler submodule structure, a wider range of applications, and higher power density. Its technical and economic advantages are significant. MMC has become the most promising topology for medium- and high-power applications such as high-voltage flexible DC transmission, medium-voltage variable speed drives, power quality improvement, and medium- and high-voltage energy storage.

[0003] Because the MMC circuit topology consists of a large number of cascaded submodules, it uses a large number of switching power devices, which are often the most prone to failure in applications. In submodules, power devices mostly use Insulated Gate Bipolar Transistors (IGBTs). IGBT faults typically include short-circuit and open-circuit faults. IGBT short-circuit faults generate strong short-circuit currents; therefore, in practical engineering, submodule overcurrent protection devices are generally installed. Once a short-circuit fault occurs, the system will quickly lock out the faulty submodule within a few microseconds to prevent shoot-through. Therefore, short-circuit faults are generally detected and protected by hardware circuitry. However, the impact of a single or a few IGBT open-circuit faults on the operation of a three-phase converter is often not immediately apparent. Appropriate fault diagnosis methods are needed to detect IGBT open-circuit faults to prevent them from developing and causing excessively high submodule capacitor voltages, severely distorted output voltage and current waveforms, and ultimately, system failure and shutdown.

[0004] Existing detection algorithms for open-circuit faults in submodules are mainly divided into three categories: hardware-based detection, data-based deep learning, and system mathematical model-based methods. Hardware-based detection methods require additional hardware circuitry for fault diagnosis. While the principle is relatively simple and the diagnosis speed is fast, this method increases hardware costs, and the presence of the added hardware itself can also constitute a potential fault point. Data-based deep learning detection methods, although fast, require a large number of training samples, have limited accuracy, and place extremely high demands on the computing performance of the main control MCU. Taking machine deep learning as an example, when using this method for submodule fault diagnosis, it is necessary to extract and analyze feature parameters from the data characteristics of normal operation and after a fault, comparing them with existing feature parameters to determine whether a fault has occurred. However, this method requires a large number of fault samples to complete the data feature tuning before diagnosis. Since IGBT module faults are in an abnormal state, relevant sample data is scarce, which causes many difficulties in practical applications. Furthermore, real-time computation of large amounts of data places extremely high demands on MCU performance, reducing the practical engineering application value. The algorithm based on the mathematical model of the system is simple and easy to implement, but the accuracy of the modeling has a great impact on its robustness. If the modeling accuracy is poor, there may be a model mismatch problem. Summary of the Invention

[0005] This invention provides a method for rapid diagnosis and location of open-circuit faults in IGBTs of converter submodules, which addresses some shortcomings of the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for rapid diagnosis and location of open circuit faults in IGBT submodules of a converter, comprising: a three-phase converter connected to the power grid, wherein each phase of the three-phase converter consists of two upper and lower bridge arms, and there are a total of six bridge arms in the three phases, and each bridge arm consists of multiple submodules connected in series and an inductor connected in series.

[0007] The method includes: fault diagnosis and fault location;

[0008] The fault diagnosis uses an adaptive extended Kalman filter algorithm to optimally estimate the three-phase circulating current and output current to determine whether a submodule open-circuit fault has occurred, and to identify the fault location of the bridge arm in the faulty phase of the three phases.

[0009] The fault location is achieved by grouping and reconstructing the sub-modules in the faulty bridge arm according to the faulty bridge arm corresponding to the faulty bridge arm, forming a reconstructed sub-unit. Then, the voltage of the reconstructed sub-unit is optimally estimated by the adaptive extended Kalman filter algorithm, and the faulty sub-module is located based on the voltage residual of the reconstructed sub-unit.

[0010] Preferably, the submodule is a half-bridge submodule, which includes: an upper transistor and a lower transistor connected in series, each of which is connected in reverse parallel with a diode, and the upper transistor and the lower transistor connected in series are connected in parallel with a capacitor.

[0011] Preferably, the fault diagnosis specifically includes the following steps:

[0012] Step 1.1: Let i be the i-th submodule in the bridge arm of the three-phase converter, initialize i = 0, and set the counter value t = 0 in the fault diagnosis; set the initial Kalman gain and reliability coefficient;

[0013] Initialize the noise variables during the three-phase circulating current process of the converter, measure the noise variables during the three-phase circulating current process of the converter, measure the noise variables during the three-phase output current process of the converter, measure the noise variables during the three-phase output current process of the converter, measure the noise variables during the sub-unit grouping and reconfiguration process, and measure the noise variables during the sub-unit grouping and reconfiguration process.

[0014] Step 1.2: Collect the three-phase bridge arm current, the DC side voltage of the converter, the three-phase upper bridge arm voltage, the three-phase lower bridge arm voltage, and the AC side three-phase output current of the converter;

[0015] Step 1.3, Calculate the three-phase circulating current of the converter.

[0016] Based on the three-phase bridge arm current, the DC side voltage of the converter, the three-phase upper bridge arm voltage, the three-phase lower bridge arm voltage, and the three-phase grid voltage, the equivalent circulating current control loop of the submodule and the equivalent AC control loop of the converter are obtained according to Kirchhoff's voltage law.

[0017] The equivalent circulating control loop expression for the submodule is as follows:

[0018]

[0019] In the above formula, L arm For the bridge arm equivalent inductance, v dc i is the DC-side voltage of the converter. a_cir i b_cir i c_cir For three-phase bridge arm circulation, u pa u pb u pc For the three-phase upper bridge arm voltage, u na u nb u nc t represents the voltage of the lower three-phase bridge arm, and t is the counter value used in fault diagnosis.

[0020] The equivalent AC control loop of the converter is expressed as follows:

[0021]

[0022] In the above formula, R arm i is the equivalent resistance of the bridge arm. sa i sb i sc The AC three-phase output current of the converter, u sa u sb u sc This refers to the three-phase power grid voltage.

[0023] Backward discretization of equation (2) yields equation (4), and backward discretization of equation (3) yields equation (5):

[0024]

[0025] In the above formula, f s i is the system sampling frequency used in the discretization process; a_cir (k), i b_cir (k), i c_cir (k) represents the three-phase bridge arm circulation at time k, i a_cir (k-1), i b_cir (k-1), i c_cir (k-1) represent the three-phase bridge arm circulation at time k-1; i sa (k), i sb (k), i sc (k) represents the three-phase output current at time k, i sa (k-1), i sb (k-1), i sc (k-1) represents the three-phase output current at time k-1; u pa (k-1), u pb (k-1), u pc (k-1) represents the three-phase upper bridge arm voltage at time k-1, u na (k-1), u nb (k-1), u nc (k-1) represents the three-phase lower bridge arm voltage at time k-1; u sa (k-1), u sb (k-1), u sc (k-1) represent the three-phase grid voltages at time k-1;

[0026] Step 1.4: Solve for the adaptive optimal state observer of the extended Kalman filter of the three-phase bridge arm circulating current according to equation (4); determine the optimal circulating current of the three-phase bridge arm based on the adaptive optimal state observer of the extended Kalman filter of the three-phase bridge arm circulating current.

[0027] Solve the adaptive optimal state observer of the extended Kalman filter for the three-phase output current according to equation (5); determine the optimal amount of the three-phase output current based on the adaptive optimal state observer of the extended Kalman filter for the three-phase output current.

[0028] Step 1.5: Based on the optimal circulating current of the three-phase bridge arm and the optimal output current of the three-phase bridge arm, calculate the residual of the circulating current of the three-phase bridge arm and the residual of the output current of the three-phase bridge arm.

[0029] If the circulating current residual and output current residual of any one of the three-phase bridge arms are both greater than or equal to the preset threshold, then proceed to step 1.6; otherwise, return to step 1.2.

[0030] Step 1.6: Clear the counter value in the fault diagnosis and perform fault diagnosis based on the positive and negative relationship between the circulating current residual and the output current residual.

[0031] Preferably, the fault location specifically includes the following steps:

[0032] Step 2.1: Based on the fault diagnosis results, obtain the fault code and reconstruct the sub-unit according to the fault code; distinguish and mark whether the fault is located in the upper arm or the lower arm; execute step 2.2 when the upper arm is faulty, and execute step 2.4 when the lower arm is faulty.

[0033] Step 2.2: Collect the voltage of the i-th submodule of the three-phase upper arm; based on the voltage of the i-th submodule of the three-phase upper arm, determine the voltage of the i-th reconfigurable subunit of the upper arm; specifically expressed as:

[0034] u Subpi =u api +u bpi +u cpi (twenty three)

[0035] In the above formula, u Subpi Let u be the voltage of the i-th reconfigurable sub-unit of the upper bridge arm. api u bpi u cpi These are the voltages of the i-th submodule of the three-phase upper bridge arm;

[0036] Equation (23) can be expressed as:

[0037]

[0038] In the above formula, C sm For the submodule capacitor, S pai S pbi S pci These represent the switching states of the i-th submodule of the three-phase upper bridge arm, i. pa i pa i pbThese are the three-phase upper bridge arm currents, and t is the counter value used in fault diagnosis.

[0039] Establish the optimal voltage estimate observer for the reconstructed sub-unit according to equation (24), and determine the optimal voltage estimate of the reconstructed sub-unit based on the optimal voltage estimate observer for the reconstructed sub-unit.

[0040] Step 2.3: Based on the optimal estimate of the reconstructed sub-unit voltage, calculate the voltage residual of the i-th reconstructed sub-unit of the upper bridge arm according to the following formula;

[0041] U Subpi_err =u Subpi_now -u Subpi (30)

[0042] In the above formula, U Subpi_err Let u be the voltage residual of the i-th reconfigured sub-unit of the upper bridge arm. Subpi_now u is the optimal estimate of the voltage of the i-th reconfiguration sub-unit of the upper bridge arm. Subpi This represents the actual sampled value of the voltage of the i-th reconfigurable subunit of the upper bridge arm.

[0043] If the voltage residual of the i-th reconfiguration sub-unit of the upper bridge arm is greater than or equal to the preset threshold of the reconfiguration sub-unit voltage, then the fault is located in the i-th reconfiguration sub-unit of the upper bridge arm. Combining the fault phase flag and fault code, it is determined that the open circuit fault of the sub-module is located in the i-th sub-module of the upper bridge arm in one of the three phases, and the fault location ends. Otherwise, proceed to step 2.2.

[0044] Step 2.4, calculate the voltage u of the lower bridge arm reconfiguration sub-unit. Subni Specifically, it is expressed as:

[0045] u Subni =u ani +u bni +u cni (31)

[0046] In the above formula, u Subni Let u be the voltage of the i-th reconfigurable sub-unit of the lower bridge arm. ani u bni u cni The voltage of the i-th submodule of the three-phase lower bridge arm;

[0047] Equation (31) can be expressed as:

[0048]

[0049] In the above formula, C sm For the submodule capacitor, S nai S nbi S nci These represent the switching states of the i-th submodule of the three-phase lower bridge arm, i na ina i nb These are the three-phase lower bridge arm currents;

[0050] The second reconstructed sub-unit voltage optimal estimation observer is established according to equation (32), and the optimal estimation value of the second reconstructed sub-unit voltage is determined based on the second reconstructed sub-unit voltage optimal estimation observer.

[0051] Step 2.5: Based on the optimal estimate of the voltage of the second reconstructed sub-unit, calculate the voltage residual of the i-th reconstructed sub-unit of the lower arm according to the following formula;

[0052] U Subni_err =u Subni_now -u Subni (38)

[0053] In the above formula, U Subni_err Let u be the voltage residual of the i-th reconfigured sub-unit of the lower bridge arm. Subni_now u is the optimal estimate of the voltage of the i-th reconfiguration sub-unit of the lower bridge arm. Subni This represents the actual sampled value of the voltage of the i-th reconstructed sub-unit of the lower bridge arm;

[0054] If the voltage residual of the i-th reconfiguration sub-unit of the lower bridge arm is greater than or equal to the preset threshold of the reconfiguration sub-unit voltage, then the fault is located in the i-th reconfiguration sub-unit of the lower bridge arm. Combining the fault phase flag and fault code, it is determined that the open circuit fault of the sub-module is located in the i-th sub-module of the lower bridge arm in one of the three phases, and the fault location ends. Otherwise, proceed to step 2.4.

[0055] The beneficial effects of this invention are:

[0056] Unlike traditional fault diagnosis methods that rely on state observers to monitor the current of each bridge arm and the capacitor voltage of all submodules, this invention, based on the extended Kalman filter algorithm, introduces residual feedback compensation of the observed quantity to the Kalman gain, obtaining an adaptive Kalman gain for the observed quantity. This solves the problem of decreased estimation accuracy of the optimal state observer under conditions such as sudden load changes. The positive and negative relationships of the residuals of the three-phase circulating current and output current are used to determine the location of the faulty phase and faulty bridge arm. Subsequently, a fault location stage based on the reconstructed subunit voltage is implemented. The three-phase submodules are grouped and reconstructed according to the location of the faulty bridge arm, and the voltage of each reconstructed subunit is optimally estimated. The faulty submodule is located based on the voltage residual of the reconstructed subunit. This avoids the problems of a large number of state observers, large data computation, and long diagnosis time when there are many submodules. It overcomes the difficulty in diagnosing open-circuit faults in half-bridge submodules in the sorting voltage equalization control algorithm, achieving rapid diagnosis and location of single IGBT open-circuit faults. Attached Figure Description

[0057] Figure 1 This is a diagram of the main circuit topology of a three-phase converter to which this invention applies;

[0058] Figure 2 This is a schematic diagram of the variables that need to be sampled in this invention;

[0059] Figure 3 This is a schematic diagram of the reconfigurable subunit proposed in this invention;

[0060] Figure 4 This is a structural diagram of the upper bridge arm reconfiguration subunit 1 proposed in this invention;

[0061] Figure 5 This is a flowchart of the steps in the method for diagnosing and locating open-circuit faults of IGBTs in a half-bridge submodule of a three-phase converter system according to the present invention. Detailed Implementation

[0062] Specific embodiments of the invention will now be described in full with reference to the accompanying drawings. For clarity, many physical details will be described in the following description. However, it should be understood that these physical details are not intended to limit the invention. That is, in some embodiments of the invention, these physical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0063] Example:

[0064] like Figure 1-5 As shown, the present invention provides a method for rapid diagnosis and location of open circuit faults in IGBT submodules of a converter, comprising: a three-phase converter connected to the power grid, wherein each phase of the three-phase converter consists of two bridge arms, and each bridge arm consists of multiple submodules connected in series and an inductor connected in series.

[0065] The method includes: fault diagnosis and fault location;

[0066] The fault diagnosis uses an adaptive extended Kalman filter algorithm to optimally estimate the three-phase circulating current and output current to determine whether a submodule open-circuit fault has occurred, and to identify the fault location of the bridge arm in the faulty phase of the three phases.

[0067] The fault location is achieved by grouping and reconstructing the sub-modules in the faulty bridge arm according to the faulty bridge arm corresponding to the faulty bridge arm, forming a reconstructed sub-unit. Then, the voltage of the reconstructed sub-unit is optimally estimated by the adaptive extended Kalman filter algorithm, and the faulty sub-module is located based on the voltage residual of the reconstructed sub-unit.

[0068] Each phase of the three-phase converter consists of two arms, upper and lower, for a total of six arms. Each arm has N MMC (Modular Multilevel Converter) submodules SM. jri(r = p, n; j = a, b, c; i = 1, 2, 3, ..., N) and a bridge arm inductor L rj Composed of series connections;

[0069] The aforementioned submodule is a half-bridge submodule, which includes: an upper transistor VT1 and a lower transistor VT2 connected in series, each of which is connected in reverse parallel with a diode, and the upper transistor VT1 and the lower transistor VT2 connected in series are connected in parallel with a capacitor.

[0070] exist Figure 1 In the MMC submodule SM jri It is a half-bridge module, consisting of the upper transistor VT1 and the lower transistor VT2 connected in series, with a power diode VD1 and a power diode VD2 connected in anti-parallel to each, and then a capacitor C connected in parallel. sm This forms a half-bridge structure. R is the DC-side resistive load, C1 and C2 are the DC-side supporting capacitors, and v dc This is the DC side voltage. j_cir For the circulation of phase j, u sj Let i be the AC grid voltage of phase j (j = a, b, or c). sj This is the grid-side output current of phase j.

[0071] The drive pulse signals of the upper transistor VT1 and the lower transistor VT2 in the same submodule are defined to be complementary. In a three-phase converter circuit, the MMC half-bridge submodule has three operating states: active, deactivated, and latched. When the upper transistor VT1 is on and the lower transistor VT2 is off, the submodule is in the active state, and the output voltage of the submodule is the voltage of the submodule capacitor, which is in a charging and discharging state. When the upper transistor VT1 is off and the lower transistor VT2 is on, the submodule is in the deactivated state, and the output voltage of the submodule is 0, and the submodule capacitor is in a bypass state. When both the upper transistor VT1 and the lower transistor VT2 are off, the submodule is in the latched state, which only occurs under abnormal operating conditions.

[0072] Figure 2 This is a schematic diagram of the variables that need to be sampled in this invention. The current i of the j-phase r-arm of the three-phase converter needs to be collected. rj The capacitor voltage u of the i-th submodule jrci The switch status signal S of the i-th submodule jri (j = a, b, c, r = p, n, i = 1, 2…N), j-phase AC grid voltage u sj and the output current i of phase j grid side sj .

[0073] Figure 3This is a schematic diagram of the reconfigurable subunit proposed in this invention. Based on the positive directions of the current in the upper (p) and lower (n) bridge arms respectively, the submodules through which the bridge arm currents flow are sequentially labeled as 1, 2, ..., N. Submodules with the same label in the three-phase upper (p) bridge arms are considered the same subunit, and are sequentially denoted as Sub. p1 Sub p2 Sub pN In the three-phase (n) bridge arms, submodules with the same designation are considered the same subunit and are sequentially denoted as Sub. n1 Sub n2 Sub nN .

[0074] Figure 4 This is a structural diagram of the upper arm reconfiguration subunit 1 proposed in this invention. The diagram shows the subunit Sub (p) of the upper arm reconfiguration. p1 For example, the upper (p) bridge arm subunit Sub after group reconstruction is shown. p1 The specific circuit structure of each sub-module.

[0075] Figure 5 This is a flowchart illustrating the steps of the method for diagnosing and locating open-circuit faults in IGBTs (Insulated-Gate Bipolar Transistors) of a three-phase converter system based on an adaptive extended Kalman filter algorithm. It details the steps of the method for diagnosing and locating single-transistor open-circuit faults in IGBTs of a three-phase converter system, including fault diagnosis and fault location. Fault diagnosis uses an adaptive extended Kalman filter algorithm to optimally estimate the circulating currents and output currents of phases a, b, and c to determine whether an open-circuit fault has occurred in the IGBT of the sub-module, and identifies the faulty phase and the faulty bridge arm. Fault location involves grouping and reconstructing the sub-units based on the faulty bridge arm, then using the adaptive extended Kalman filter algorithm to optimally estimate the voltage of the reconstructed sub-units, and locating the faulty sub-module based on the voltage residuals of the reconstructed sub-units.

[0076] The aforementioned fault diagnosis specifically includes the following steps:

[0077] Step 1.1: Let i be the i-th submodule in the bridge arm of the three-phase converter, initialize i = 0, and set the counter value t = 0 in fault diagnosis; set the initial Kalman gain K. a_cir K b_cir K c_cir K a K b K c K Subpi K Subni Circulation reliability coefficient α cir α, αSubp α Subn ;

[0078] Let the three-phase circulating current threshold of the converter be I. a_cir_th I b_cir_th I c_cir_th The three-phase output current threshold of the converter is I. a_th I b_th I c_th The fault diagnosis duration threshold is T. th The fault location duration threshold is T. th_Sub ; Reconstruct submodule voltage threshold U sub_th The autocovariance of the error in the three-phase bridge arm circulating current estimation is P. a_cir_mid P b_cir_mid P c_cir_mid The autocovariance of the error in the optimal estimation of the three-phase bridge arm circulating current is P. a_cir_now P b_cir_now P c_cir_now The autocovariance of the error in estimating the three-phase output current of the converter is P. a_mid P b_mid P c_mid The autocovariance of the error in the optimal estimation of the three-phase output current of the converter is P. a_now P b_now P c_now The autocovariance of the voltage estimation error of the i-th reconfiguration submodule of the upper bridge arm is P. Subpi_mid The autocovariance of the error in the optimal voltage estimation of the i-th reconfiguration submodule of the upper bridge arm is P. Subpi_now The autocovariance of the voltage estimation error of the i-th reconstructed sub-unit of the lower bridge arm is P. Subni_mid The autocovariance P of the error in the optimal estimation of the voltage of the i-th reconstructed sub-unit of the lower bridge arm Subni_now ;

[0079] Initialize the noise variable Q of the three-phase circulating current process of the converter a_cir Q b_cir Q c_cir The noise variable R of the three-phase circulating current of the converter is measured. a_cir R a_cir R a_cir The noise variable Q of the three-phase output current of the converter a Q b Q c The noise variable R of the three-phase output current of the converter is measured. a R b R c Noise variable Q during sub-unit grouping and reconfiguration process Subp Q Subn The noise variable R measured during the sub-unit grouping and reconstruction process Subp RSubn ;

[0080] Step 1.2: Collect the upper arm current i of the three-phase bridge. pa i pb i pc and lower bridge arm current i na i nb i nc The switch status S of each submodule of the upper bridge arm jpi and the switch status S of each submodule of the lower bridge arm jni The capacitor voltage u of each submodule in the upper bridge arm jpci and the capacitor voltage u of each submodule in the lower bridge arm jnci DC side voltage of the converter v dc The AC output current i of the converter sa i sb i sc Grid voltage u sa u sb u sc ;

[0081] Step 1.3, calculate the three-phase circulating currents a, b, and c according to equation (1);

[0082]

[0083] The equivalent circulating current control loop of the submodule is obtained according to Kirchhoff's voltage law, as shown in equation (2):

[0084]

[0085] In the above formula, L arm For the bridge arm equivalent inductance, v dc i is the DC-side voltage of the converter. a_cir i b_cir i c_cir For three-phase bridge arm circulation, u pa u pb u pc For the three-phase upper bridge arm voltage, u na u nb u nc This refers to the voltage of the lower three-phase bridge arm.

[0086] Similarly, the equivalent AC control loop of the converter is obtained from Kirchhoff's voltage law, as shown in equation (3):

[0087]

[0088] In the above formula, L arm R is the equivalent inductance of the bridge arm. arm i is the equivalent resistance of the bridge arm. sa isb i sc The AC three-phase output current of the converter, u pa u pb u pc For the three-phase upper bridge arm voltage, u na u nb u nc For the three-phase lower bridge arm voltage, u sa u sb u sc This refers to the three-phase power grid voltage.

[0089] Backward difference discretization of equations (2) and (3) yields:

[0090]

[0091] In the above formula, L arm R is the equivalent inductance of the bridge arm. arm f is the equivalent resistance of the bridge arm. s i is the system sampling frequency used in the discretization process; a_cir (k), i b_cir (k), i c_cir (k) represents the three-phase bridge arm circulation at time k, i a_cir (k-1), i b_cir (k-1), i c_cir (k-1) represent the three-phase bridge arm circulation at time k-1; i sa (k), i sb (k), i sc (k) represents the three-phase output current at time k, i sa (k-1), i sb (k-1), i sc (k-1) represents the three-phase output current at time k-1; u pa (k-1), u pb (k-1), u pc (k-1) represents the three-phase upper bridge arm voltage at time k-1, u na (k-1), u nb (k-1), u nc (k-1) represents the three-phase lower bridge arm voltage at time k-1; u sa (k-1), u sb (k-1), u sc (k-1) represent the three-phase grid voltages at time k-1;

[0092] Step 1.4: Solve for the adaptive optimal state observer of the extended Kalman filter for the three-phase bridge arm circulating current according to equation (4); determine the optimal circulating current of the three-phase bridge arm based on the adaptive optimal state observer of the extended Kalman filter for the three-phase bridge arm circulating current; specifically as follows:

[0093] ①The relationship between the output voltage of the i-th submodule of each phase upper and lower bridge arm, the capacitor voltage, and the switch state is as follows:

[0094]

[0095] In the formula, u jpi u jni These are the output voltages of the i-th submodule of the upper and lower bridge arms of phase j, respectively; S jpi S jni These represent the switching states of the i-th submodule of the upper and lower arms of phase j, respectively, where 1 indicates on and 0 indicates off; u jpci u jnci These are the capacitor voltages of the i-th submodules in the upper and lower arms of phase j, respectively.

[0096] And the state equation for the capacitor voltage of the i-th submodule in each bridge arm is:

[0097]

[0098] In the above formula, C sm For the submodule capacitor, i pj i nj The currents are for the upper and lower bridge arms.

[0099] According to equation (6), the voltage output value u of each phase upper and lower bridge arm at time k can be obtained. pj u nj :

[0100]

[0101] ② Calculate the estimated values ​​of the three-phase bridge arm circulation state at time k:

[0102]

[0103] Among them, i a_cir_mid i b_cir_mid i c_cir_mid These are the estimated circulating current values ​​for the three-phase bridge arms a, b, and c, respectively, and i a_cir_now i b_cir_now i c_cir_now These are the optimal estimates of the circulating current in the three-phase bridge arms a, b, and c, respectively.

[0104] ③ Calculate the prediction error covariance at time k:

[0105]

[0106] Among them, P a_cir_mid P b_cir_mid P c_cir_mid The autocovariance of the error in estimating the circulating current of the three-phase bridge arms a, b, and c are given by P. a_cir_now P b_cir_now P c_cir_now The error autocovariances of the optimal estimation of the circulating currents in the three-phase bridge arms a, b, and c are Q. a_cir Q b_cir Q c_cir The noise variables in the three-phase circulating current process of converters a, b, and c are given.

[0107] ④ Calculate the Kalman gain at time k:

[0108]

[0109] Among them, K a_cir K b_cir K c_cir The adaptive Kalman gain after introducing the respective circulating residuals of the three-phase circulating currents a, b, and c are given by R. a_cir R b_cir R c_cir For the three-phase circulating current measurement of converters a, b, and c, α cir The set recirculation reliability coefficient.

[0110] ⑤ Calculate the optimal estimates of the three-phase bridge arm circulation at time k:

[0111]

[0112] Among them, i a_cir i b_cir i c_cir These are the a, b, and c phase arm circulation currents calculated according to equation (1).

[0113] ⑥ Update the prediction estimation error covariance at time k:

[0114]

[0115] Where: K a_cir K b_cir K c_cir The adaptive Kalman gain P is the sum of the residuals of the three-phase circulating currents a, b, and c after introducing their respective circulating currents. a_cir_mid P b_cir_mid P c_cir_mid The autocovariance of the error in estimating the circulating current of the three-phase bridge arms a, b, and c are given by P. a_cir_now P b_cir_now P c_cir_nowThese are the autocovariances of the error in the optimal estimation of the circulating current of the three-phase bridge arms a, b, and c, respectively.

[0116] Thus, an adaptive optimal state observer based on extended Kalman filtering was designed to achieve the optimal estimation process of the circulating current in the three-phase bridge arms a, b, and c.

[0117] The adaptive optimal state observer of the extended Kalman filter for the three-phase output current is obtained according to equation (5); based on the adaptive optimal state observer of the extended Kalman filter for the three-phase output current, the optimal value of the three-phase output current is determined; specifically as follows:

[0118] ① Calculate the estimated values ​​of the three-phase output currents a, b, and c at time k:

[0119]

[0120] Among them, i sa_mid i sb_mid i sc_mid These are the estimated output currents for phases a, b, and c, respectively, and i sa_now i sb_now i sc_now These are the optimal estimated values ​​of the output current for phases a, b, and c, respectively.

[0121] ② Calculate the prediction error covariance at time k:

[0122]

[0123] Among them, P a_mid P b_mid P c_mid The autocovariance of the estimation error for the three-phase output currents a, b, and c are respectively, P. a_now P b_now P c_now The autocovariance of the error for the optimal estimation of the output currents of phases a, b, and c are respectively, Q. a Q b Q c The noise variables in the output current process of the three phases a, b, and c are denoted as .

[0124] ④ Calculate the Kalman gain at time k:

[0125]

[0126] Among them, K a K b K c The adaptive Kalman gain for the three-phase output currents a, b, and c are respectively, R a R b R cThe noise variable is measured for the three-phase output currents a, b, and c, where α is the set output current reliability coefficient.

[0127] ⑤ Calculate the optimal estimated values ​​of the three-phase output currents a, b, and c at time k:

[0128]

[0129] Among them, i sa i sb i sc These are the actual sampled output currents of phases a, b, and c.

[0130] ⑥ Update the prediction estimation error covariance at time k:

[0131]

[0132] Where: K a K b K c The adaptive Kalman gain for the three-phase output currents a, b, and c are respectively, P a_mid P b_mid P c_mid The autocovariance of the estimation error for the three-phase output currents a, b, and c are respectively, P. a_now P b_now P c_now These are the autocovariances of the optimal estimates of the output currents of phases a, b, and c, respectively.

[0133] Thus, an adaptive optimal state observer based on extended Kalman filtering was designed to achieve the optimal estimation process of the three-phase output currents a, b, and c.

[0134] Step 1.5: Based on the converter, calculate the three-phase arm circulating current residual I. a_cir_err I b_cir_err I c_cir_err Calculate the three-phase output current residual I a_err I b_err I c_err ;

[0135] If the absolute value of the circulating current residual and the absolute value of the output current residual of a certain phase (j = a, b, c) in the three phases are different from the set circulating current threshold I... j_cir_th Output current threshold I j_th The magnitude relationship is determined by the relative magnitudes of the fault current and output current. If the circulating current residual and output current residual of the bridge arm are both greater than or equal to the preset threshold, the corresponding fault phase flag is set to 1, and step 1.6 is executed; otherwise, the fault phase flag is set to 0, and the process returns to step 1.2.

[0136] The residual current I of the three-phase bridge arm circulation I of phases a, b, and c is calculated using equation (19). a_cir_err Ib_cir_err I c_cir_err The residual I of the three-phase output currents a, b, and c is calculated using equation (20). a_err I b_err I c_err .

[0137]

[0138] Based on equation (21), determine the absolute value of the circulating current residual and the absolute value of the output current residual of phase j (j = a, b, c) and compare them with the set circulating current threshold I. j_cir_th Output current threshold I j_th The magnitude relationship. If the residual current of phase j and the residual current of output current are both greater than or equal to the set threshold, then the corresponding fault phase flag will be set. j Set (j = a, b, c) to 1 and execute step 1.6; otherwise, set the fault phase flag. j Set (j = a, b, c) to 0, then return to step 1.2.

[0139]

[0140] Step 1.6: Clear the counter value in the fault diagnosis and perform fault diagnosis based on the positive and negative relationship between the circulating current residual and the output current residual.

[0141] Fault diagnosis is performed based on the positive and negative relationships between the circulating current residual and the output current residual. The fault code is denoted as Fault_flag. j The specific fault diagnosis and discrimination relationship is shown in equation (22):

[0142]

[0143] In the formula, Fault_flag j =1 indicates an open-circuit fault in the VT1 switch of the submodule in phase j (p) of the bridge arm; Fault_flag j =2 indicates an open-circuit fault in the VT2 switch of the submodule on the (p) arm of phase j; Fault_flag j =3 indicates that the VT1 switch in the submodule of the j-phase lower (n) bridge arm has an open-circuit fault; Fault_flag j =4 indicates an open-circuit fault in the VT2 switch of the lower (n) arm of phase j. At this point, the open-circuit fault can be initially located in the r (r=p,n) arm of phase j, and it can be determined whether it is an open-circuit fault of VT1 or VT2. Then, the fault location process can begin.

[0144] The fault location specifically includes the following steps:

[0145] Step 2.1: Based on the fault diagnosis results, obtain the fault code and reconstruct the sub-unit according to the fault code; distinguish and mark whether the fault is located in the upper arm or the lower arm; execute step 2.2 when the upper arm is faulty, and execute step 2.4 when the lower arm is faulty.

[0146] Based on the fault code Fault_flag j Reconfigure the three-phase MMC subunit. If the fault code is Fault_flag... j =1 or 2, then the fault is located in the upper bridge arm. Taking the positive direction of the upper bridge arm current as a reference, the sub-modules through which the bridge arm current flows are sequentially labeled as 1, 2, ..., N. Sub-modules with the same label in the upper bridge arm of phases a, b, and c are considered to be the same sub-unit and are sequentially denoted as Sub. p1 Sub p2 Sub pN If the fault code is Fault_flag j =3 or 4, then the fault is located in the lower bridge arm. Taking the positive direction of the lower bridge arm current as a reference, the sub-modules through which the bridge arm current flows are sequentially labeled as 1, 2, ..., N. Sub-modules with the same label in the a, b, c phase lower bridge arm are considered as the same sub-unit and are sequentially denoted as Sub. n1 Sub n2 Sub nN .

[0147] Step 2.2: Collect the voltage of the i-th submodule of the three-phase upper arm; based on the voltage of the i-th submodule of the three-phase upper arm, determine the voltage of the i-th reconfigurable subunit of the upper arm; specifically expressed as:

[0148] u Subpi =u api +u bpi +u cpi (twenty three)

[0149] In the above formula, u Subpi Let u be the voltage of the i-th reconfigurable sub-unit of the upper bridge arm. api u bpi u cpi These are the voltages of the i-th submodule of the three-phase upper bridge arm;

[0150] Equation (23) can be expressed as:

[0151]

[0152] In the above formula, C sm For the submodule capacitor, S pai S pbi S pci These represent the switching states of the i-th submodule of the three-phase upper bridge arm, i. pa i pai pb These are the three-phase upper bridge arm currents, and t is the counter value used in fault diagnosis.

[0153] A voltage optimal estimation observer for the reconstructed sub-unit is established according to equation (24). Based on the voltage optimal estimation observer for the reconstructed sub-unit, the optimal estimated value of the voltage of the reconstructed sub-unit is determined; specifically as follows:

[0154] ① Calculate the estimated value of the voltage of the i-th reconstructed sub-cell at time k:

[0155]

[0156] Among them, u Subpi_mid u is the estimated voltage of the i-th reconfigured sub-unit of the upper bridge arm. Subpi_now This is the optimal estimate of the voltage of the i-th reconfigurable sub-unit of the upper bridge arm.

[0157] ② Calculate the prediction error covariance at time k:

[0158] P Subpi_mid (k)=P Subpi_now (k-1)+Q Subp (26)

[0159] Among them, P Subpi_mid Let P be the autocovariance of the voltage estimation error of the i-th reconfiguration sub-unit of the upper bridge arm. Subpi_now Let Q be the autocovariance of the error in the optimal estimation of the voltage of the i-th reconfiguration sub-unit of the upper bridge arm. Subp The process noise variable is used to reconstruct the voltage of the sub-unit of the upper bridge arm.

[0160] ③ Calculate the Kalman gain at time k:

[0161]

[0162] Among them, K Subpi R is the adaptive Kalman gain of the voltage of the i-th reconstructed sub-unit in the upper bridge arm. Subp For the measurement noise variable of the upper arm reconfiguration sub-unit voltage, α Subp The voltage reliability coefficient of the upper bridge arm reconfiguration subunit is set.

[0163] ④ Calculate the optimal estimate of the voltage of the i-th reconstructed sub-unit at time k:

[0164] u Subpi_now (k)=u Subpi_mid (k)+K Subpi (k)·[u Subpi (k)-u Subpi_mid (k)] (28)

[0165] Among them, u SubpiThe voltage of the i-th reconfiguration sub-unit of the upper bridge arm is calculated according to equation (23).

[0166] ⑤ Calculate the covariance of the prediction estimation error at time k:

[0167] P Subpi_now (k)=[1-K Subpi (k)]·P Subpi_mid (k) (29)

[0168] Where: K Subpi P is the adaptive Kalman gain of the voltage of the i-th reconstructed sub-unit in the upper bridge arm. Subpi_mid Let P be the autocovariance of the voltage estimation error of the i-th reconfiguration sub-unit of the upper bridge arm. Subpi_now Let be the autocovariance of the error in the optimal estimation of the voltage of the i-th reconfigurable sub-unit of the upper bridge arm.

[0169] At this point, the design of the optimal state observer for the reconfigurable subunit voltage of the upper bridge arm is complete.

[0170] Step 2.3: Based on the optimal estimate of the reconstructed sub-unit voltage, calculate the voltage residual of the i-th reconstructed sub-unit of the upper bridge arm according to the following formula;

[0171] U Subpi_err =u Subpi_now -u Subpi (30)

[0172] In the above formula, U Subpi_err Let u be the voltage residual of the i-th reconfigured sub-unit of the upper bridge arm. Subpi_now u is the optimal estimate of the voltage of the i-th reconfiguration sub-unit of the upper bridge arm. Subpi This represents the actual sampled value of the voltage of the i-th reconfigurable subunit of the upper bridge arm.

[0173] If the voltage residual of the i-th reconfiguration subunit of the upper bridge arm is U Subpi_err The voltage of the reconfigurable sub-unit is greater than or equal to the preset threshold U. sub_th And the duration exceeds T th_Sub Then, the fault is located in the i-th reconfiguration sub-unit of the upper arm, combined with the fault phase flag and the fault code Fault_flag. j If the open circuit fault of the submodule is determined to be located in the i-th submodule of the upper arm of one of the three phases j (j = a, b, c), the fault location ends; otherwise, proceed to step 2.2.

[0174] Step 2.4, calculate the voltage u of the lower bridge arm reconfiguration sub-unit. Subni Specifically, it is expressed as:

[0175] u Subni =u ani +u bni +ucni (31)

[0176] In the above formula, u Subni Let u be the voltage of the i-th reconfigurable sub-unit of the lower bridge arm. ani u bni u cni The voltage of the i-th submodule of the three-phase lower bridge arm;

[0177] Equation (31) can be expressed as:

[0178]

[0179] In the above formula, C sm For the submodule capacitor, S nai S nbi S nci These represent the switching states of the i-th submodule of the three-phase lower bridge arm, i na i na i nb These are the three-phase lower bridge arm currents;

[0180] The second reconstructed sub-unit voltage optimal estimation observer is established according to equation (32). Based on the second reconstructed sub-unit voltage optimal estimation observer, the optimal estimated value of the second reconstructed sub-unit voltage is determined; specifically as follows:

[0181] ① Calculate the voltage estimate of the i-th reconstructed sub-cell at time k:

[0182]

[0183] Among them, u Subni_mid u is the estimated voltage of the i-th reconfigured sub-unit of the lower bridge arm. Subni_now This is the optimal estimate of the voltage of the i-th reconfigurable sub-unit of the lower bridge arm.

[0184] ② Calculate the prediction error covariance at time k:

[0185] P Subni_mid (k)=P Subni_now (k-1)+Q Subn (34)

[0186] Among them, P Subni_mid Let P be the autocovariance of the voltage estimation error of the i-th reconfiguration sub-unit of the lower bridge arm. Subni_now Let Q be the autocovariance of the error in the optimal estimation of the voltage of the i-th reconfiguration sub-unit of the lower bridge arm. Subn The process noise variable is the voltage of the reconstructed sub-unit of the lower bridge arm.

[0187] ③ Calculate the Kalman gain at time k:

[0188]

[0189] Among them, K Subni R is the adaptive Kalman gain of the voltage of the i-th reconstructed sub-unit in the lower bridge arm. Subn α is the measurement noise variable for the voltage of the lower bridge arm reconfiguration sub-unit. Subn The reliability coefficient for the reconfigurable subunit voltage of the lower bridge arm.

[0190] ④ Calculate the optimal estimate of the voltage of the i-th reconstructed sub-unit at time k:

[0191] u Subni_now (k)=u Subni_mid (k)+K Subni (k)·[u Subni (k)-u Subni_mid (k)] (36)

[0192] Among them, u Subni The voltage of the i-th reconfiguration sub-unit of the lower bridge arm is calculated according to equation (31).

[0193] ⑤ Calculate the covariance of the prediction estimation error at time k:

[0194] P Subni_now (k)=[1-K Subni (k)]·P Subni_mid (k) (37)

[0195] Where: K Subni P is the adaptive Kalman gain of the voltage of the i-th reconstructed sub-unit in the lower bridge arm. Subni_mid Let P be the autocovariance of the voltage estimation error of the i-th reconfiguration sub-unit of the lower bridge arm. Subni_now Let be the autocovariance of the error in the optimal estimation of the voltage of the i-th reconfigurable sub-unit of the lower bridge arm.

[0196] At this point, the design of the optimal state observer for the voltage of the lower bridge arm reconfiguration subunit is complete.

[0197] Step 2.5: Based on the optimal estimate of the voltage of the second reconstructed sub-unit, calculate the voltage residual of the i-th reconstructed sub-unit of the lower arm according to the following formula;

[0198] U Subni_err =u Subni_now -u Subni (38)

[0199] In the above formula, U Subni_err Let u be the voltage residual of the i-th reconfigured sub-unit of the lower bridge arm. Subni_now u is the optimal estimate of the voltage of the i-th reconfiguration sub-unit of the lower bridge arm. Subni This represents the actual sampled value of the voltage of the i-th reconstructed sub-unit of the lower bridge arm;

[0200] If the voltage residual of the i-th reconfiguration sub-unit in the lower arm is greater than or equal to the preset threshold for the reconfiguration sub-unit voltage, then the fault is located in the i-th reconfiguration sub-unit in the lower arm, combined with the fault phase flag and the fault code Fault_flag. j If the open circuit fault of the submodule is determined to be located in the i-th submodule of the lower arm of one of the three phases j (j = a, b, c), the fault location ends; otherwise, proceed to step 2.4.

[0201] This invention presents a rapid diagnosis method for open-circuit faults in IGBTs of a three-phase converter half-bridge submodule based on an adaptive optimal state observer using extended Kalman filtering, and a method for locating IGBT open-circuit fault submodules using the residual of reconstructed sub-unit voltages. This fault diagnosis method improves the dynamic response and robustness of the optimal estimation observer by introducing the residual between the optimal estimate and the measured value into the Kalman gain. The observer performs optimal state estimation of the three-phase circulating current and output current, and uses the positive or negative relationship of the residual between the optimal estimate and the actual sampled value to diagnose the faulty phase and faulty bridge arm location. After determining the faulty bridge arm location, the submodules are grouped and reconstructed according to the faulty bridge arm location, and the faulty submodule is located using the residual value of the reconstructed sub-unit voltage. Using the method proposed in this invention, when a single or multiple IGBT open-circuit faults occur in a three-phase MMC, the faulty submodule can be diagnosed and located quickly and accurately. It also solves the problem of being unable to identify the faulty submodule when using a sorting algorithm to control the capacitor voltage balancing of the submodules.

[0202] The above description is merely a specific embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for rapid diagnosis and location of open-circuit faults in IGBTs of a converter submodule, characterized in that, include: A three-phase converter connected to the power grid, wherein each phase of the three-phase converter consists of two bridge arms, one upper and one lower, and each bridge arm consists of multiple sub-modules connected in series and an inductor connected in series; The method includes: fault diagnosis and fault location; The fault diagnosis uses an adaptive extended Kalman filter algorithm to optimally estimate the three-phase circulating current and output current to determine whether a submodule open-circuit fault has occurred, and to identify the fault location of the bridge arm in the faulty phase of the three phases. The fault location is achieved by grouping and reconstructing the sub-modules in the faulty bridge arm according to the faulty bridge arm corresponding to the faulty bridge arm, forming a reconstructed sub-unit. Then, the voltage of the reconstructed sub-unit is optimally estimated by the adaptive extended Kalman filter algorithm, and the faulty sub-module is located based on the voltage residual of the reconstructed sub-unit. The fault diagnosis specifically includes the following steps: Step 1.1: Let i be the i-th submodule in the bridge arm of the three-phase converter, initialize i=0, and set the counter value t=0 in fault diagnosis; set the initial Kalman gain and reliability coefficient; Initialize the noise variables during the three-phase circulating current process of the converter, the noise variables during the measurement of the three-phase circulating current of the converter, the noise variables during the process of the three-phase output current of the converter, the noise variables during the measurement of the three-phase output current of the converter, the noise variables during the sub-unit grouping and reconfiguration process, and the measurement noise variables during the sub-unit grouping and reconfiguration process. Step 1.2: Collect the three-phase bridge arm current, the DC side voltage of the converter, the three-phase upper bridge arm voltage, the three-phase lower bridge arm voltage, and the AC side three-phase output current of the converter; Step 1.3: Calculate the three-phase circulating current of the converter; based on the three-phase arm current, the DC side voltage of the converter, the three-phase upper arm voltage, the three-phase lower arm voltage, and the three-phase grid voltage, obtain the equivalent circulating current control loop of the submodule and the equivalent AC control loop of the converter according to Kirchhoff's voltage law; The equivalent circulating control loop expression for the submodule is as follows: （2）； In the above formula, L arm For the bridge arm equivalent inductance, v dc i is the DC-side voltage of the converter. a_cir i b_cir i c_cir For three-phase bridge arm circulation, u pa u pb u pc For the three-phase upper bridge arm voltage, u na u nb u nc This refers to the voltage of the lower three-phase bridge arm. The equivalent AC control loop of the converter is expressed as follows: （3）； In the above formula, R arm i is the equivalent resistance of the bridge arm. sa i sb i sc The AC three-phase output current of the converter, u sa u sb u sc This refers to the three-phase power grid voltage. Backward discretization of equation (2) yields equation (4), and backward discretization of equation (3) yields equation (5): ； ； In the above formula, , f s i is the system sampling frequency used in the discretization process; a_cir (k), i b_cir (k), i c_cir (k) represents the three-phase bridge arm circulation at time k, i a_cir (k-1), i b_cir (k-1), i c_cir (k-1) represent the three-phase bridge arm circulation at time k-1; i sa (k), i sb (k), i sc (k) represents the three-phase output current at time k, i sa (k-1), i sb (k-1), i sc (k-1) represents the three-phase output current at time k-1; u pa (k-1), u pb (k-1), u pc (k-1) represents the three-phase upper bridge arm voltage at time k-1, u na (k-1), u nb (k-1), u nc (k-1) represents the three-phase lower bridge arm voltage at time k-1; u sa (k-1), u sb (k-1), u sc (k-1) represent the three-phase grid voltages at time k-1; Step 1.4: Solve for the adaptive optimal state observer of the extended Kalman filter of the three-phase bridge arm circulating current according to equation (4); determine the optimal circulating current of the three-phase bridge arm based on the adaptive optimal state observer of the extended Kalman filter of the three-phase bridge arm circulating current. Solve the adaptive optimal state observer of the extended Kalman filter for the three-phase output current according to equation (5); determine the optimal amount of the three-phase output current based on the adaptive optimal state observer of the extended Kalman filter for the three-phase output current. Step 1.5: Based on the optimal circulating current of the three-phase bridge arm and the optimal output current of the three-phase bridge arm, calculate the residual of the circulating current of the three-phase bridge arm and the residual of the output current of the three-phase bridge arm. If the circulating current residual and output current residual of any one of the three-phase bridge arms are both greater than or equal to the preset threshold, then proceed to step 1.6; otherwise, return to step 1.

2. Step 1.6: Clear the counter value in the fault diagnosis and perform fault diagnosis based on the positive and negative relationship between the circulating current residual and the output current residual; The fault location specifically includes the following steps: Step 2.1: Based on the fault diagnosis results, obtain the fault code and reconstruct the sub-unit according to the fault code; distinguish and mark the fault location in the upper arm and the lower arm; execute step 2.2 when the upper arm is faulty, and execute step 2.4 when the lower arm is faulty. Step 2.2: Collect the voltage of the i-th submodule of the three-phase upper arm; based on the voltage of the i-th submodule of the three-phase upper arm, determine the voltage of the i-th reconfigurable subunit of the upper arm; specifically expressed as: （23）； In the above formula, u Subpi Let u be the voltage of the i-th reconfigurable sub-unit of the upper bridge arm. api u bpi u cpi These are the voltages of the i-th submodule of the three-phase upper bridge arm; Equation (23) can be expressed as: ； In the above formula, For the submodule capacitor, S pai S pbi S pci These represent the switching states of the i-th submodule of the three-phase upper arm, i. pa i pa i pb These are the currents of the three-phase upper bridge arms; Establish the optimal voltage estimate observer for the reconstructed sub-unit according to equation (24), and determine the optimal voltage estimate of the reconstructed sub-unit based on the optimal voltage estimate observer for the reconstructed sub-unit. Step 2.3: Based on the optimal estimate of the reconstructed sub-unit voltage, calculate the voltage residual of the i-th reconstructed sub-unit of the upper bridge arm according to the following formula; ； In the above formula, U Subpi_err For the voltage residual of the i-th reconstructed sub-unit of the upper bridge arm, This represents the optimal voltage estimate for the i-th reconfigurable sub-unit of the upper bridge arm. This represents the actual sampled value of the voltage of the i-th reconfigurable sub-unit of the upper bridge arm; If the voltage residual of the i-th reconfiguration sub-unit of the upper bridge arm is greater than or equal to the preset threshold of the reconfiguration sub-unit voltage, then the fault is located in the i-th reconfiguration sub-unit of the upper bridge arm. Combining the fault phase flag and fault code, it is determined that the open circuit fault of the sub-module is located in the i-th sub-module of the upper bridge arm in one of the three phases, and the fault location ends. Otherwise, proceed to step 2.

2. Step 2.4, calculate the voltage u of the lower bridge arm reconfiguration sub-unit. Subni Specifically, it is expressed as: ； In the above formula, u Subni Let u be the voltage of the i-th reconfigurable sub-unit of the lower bridge arm. ani u bni u cni The voltage of the i-th submodule of the three-phase lower bridge arm; Equation (31) can be expressed as: ； In the above formula, For the submodule capacitor, S nai S nbi S nci These represent the switching states of the i-th submodule of the three-phase lower bridge arm, i na i na i nb These are the three-phase lower bridge arm currents; The second reconstructed sub-unit voltage optimal estimation observer is established according to equation (32), and the optimal estimation value of the second reconstructed sub-unit voltage is determined based on the second reconstructed sub-unit voltage optimal estimation observer. Step 2.5: Based on the optimal estimate of the voltage of the second reconstructed sub-unit, calculate the voltage residual of the i-th reconstructed sub-unit of the lower arm according to the following formula; ； In the above formula, U Subni_err Let u be the voltage residual of the i-th reconfigured sub-unit of the lower bridge arm. Subni_now u is the optimal estimate of the voltage of the i-th reconfiguration sub-unit of the lower bridge arm. Subni This represents the actual sampled value of the voltage of the i-th reconstructed sub-unit of the lower bridge arm; If the voltage residual of the i-th reconfiguration sub-unit of the lower bridge arm is greater than or equal to the preset threshold of the reconfiguration sub-unit voltage, then the fault is located in the i-th reconfiguration sub-unit of the lower bridge arm. Combining the fault phase flag and fault code, it is determined that the open circuit fault of the sub-module is located in the i-th sub-module of the lower bridge arm in one of the three phases, and the fault location ends. Otherwise, proceed to step 2.

4.

2. The method according to claim 1, characterized in that, The submodule is a half-bridge submodule, which includes: an upper transistor and a lower transistor connected in series, each of which is connected in reverse parallel with a diode, and the upper transistor and the lower transistor connected in series are connected in parallel with a capacitor.

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