Fault-tolerant control method for duplex-winding steer-by-wire system based on prediction model

Abstract

The invention discloses a fault-tolerant control method for a duplex-winding steer-by-wire system based on a prediction model, and the method comprises the steps: designing an open-phase fault diagnosis method, carrying out the fault diagnosis of a duplex-winding motor, and obtaining a fault diagnosis result; judging the health state of the double-winding motor according to the fault diagnosis result, establishing a double-winding motor prediction model in the health state, and reconstructing the double-winding motor prediction model in the open-phase fault state; and superposing the control input voltage in the nominal state and the auxiliary control input to jointly act on the double-winding motor, thereby realizing stability control of the double-winding motor in a healthy state and an open-phase fault state. According to the control method, it can be guaranteed that the dual-winding steering motor has fault-tolerant capability when the dual-winding steering motor has a local failure fault, so that the steer-by-wire system can effectively isolate and actively reconstruct a fault point according to the stability condition, and the control accuracy, stability and high safety under the condition of the local failure of the steering motor are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile steering systems, and specifically refers to a fault-tolerant control method of a dual-winding wire-controlled steering system based on a prediction model. Background Art

[0002] The steer-by-wire system eliminates the mechanical connection components between the steering wheel and the steered wheels, completely getting rid of the limitations of mechanical firmware and achieving steering entirely by electrical energy. It not only has all the advantages of traditional mechanical steering systems, but can also optimize angular transfer characteristics that are difficult to achieve with mechanical systems.

[0003] The actuator motor of the existing wire-controlled steering system adopts a dual-winding motor, which is composed of two sets of three-phase windings. The two sets of windings are electrically independent and do not affect each other during normal operation. When a fault occurs, the stability of the system and good fault tolerance performance can be improved.

[0004] However, when a dual-winding motor has a phase-loss fault, the faulty phase needs to be diagnosed and fault-tolerantly controlled. There are few existing research methods on active fault-tolerant control of dual-winding motors. Chinese invention patent application number CN202111646267.4 discloses a dual-motor wire-controlled steering system and a convolutional neural network fault-tolerant control method thereof, which uses a convolutional neural network method to perform real-time fault detection of the dual-motor wire-controlled steering system, but it does not take into account the changes in the dual-winding motor model under the phase-loss fault state. Chinese invention patent application number CN202211481201.9 discloses a dual-motor wire-controlled steering system and an active fault-tolerant control method thereof, which compares the control torque output by the dual-motor torque sensor with that output by the front wheel angle tracking controller, calculates the fault coefficient, and optimizes the steering actuator model to a variable parameter nonlinear structure containing motor fault parameters, but it does not consider the influence of time-varying parameters on tracking control after the fault occurs. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a fault-tolerant control method for a dual-winding wire-controlled steering system based on a prediction model, so as to solve the problems of inaccurate fault motor model and low accuracy of fault-tolerant control strategy in the existing dual-winding wire-controlled steering system technology. The control method of the present invention can ensure that the dual-winding steering motor has fault tolerance when a local failure occurs, so that the wire-controlled steering system can effectively isolate and actively reconstruct the fault point according to the stability condition, thereby improving the accuracy, stability and high safety of the control in the case of a local failure of the steering motor.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A fault-tolerant control method for a dual-winding wire-controlled steering system based on a prediction model of the present invention comprises the following steps:

[0008] Step 1): Design a phase-loss fault diagnosis method, perform fault diagnosis on the dual-winding motor, and obtain a fault diagnosis result;

[0009] Step 2): judging the health status of the dual-winding motor according to the fault diagnosis result of step 1); if the dual-winding motor is in a healthy state, establishing a prediction model of the dual-winding motor in a healthy state; if the dual-winding motor is in a phase-loss fault state, reconstructing a prediction model of the dual-winding motor in a phase-loss fault state;

[0010] Step 3): According to the dual-winding motor prediction model in step 2), solve the objective function to obtain the control input voltage of the nominal state; use the actual state of the dual-winding motor and the updated Tube invariant set to update the objective function to solve the control input voltage of the nominal state at time k+i, and generate the auxiliary control input at time k+i; superimpose the control input voltage of the nominal state at time k+i and the auxiliary control input at time k+i and act on the dual-winding motor together to achieve stability control of the dual-winding motor in a healthy state and a phase-loss fault state.

[0011] Furthermore, the step 1) specifically includes:

[0012] Step 11): Design the dq axis current judgment condition for phase failure: If the dq axis current i d =0,i q =I m , then the dual-winding motor is in a healthy state; if the dq axis current i′ d ≠0, i q ′≠I m , then the dual-winding motor is in a phase-loss fault state, i d 、i q are the direct axis current and quadrature axis current in the synchronous rotating coordinate system under the healthy state, i′ d 、i q ′ are the direct-axis current and quadrature-axis current in the synchronous rotating coordinate system under the phase failure state, I m is the amplitude of the stator current;

[0013] Step 12): Design the judgment condition of the phase loss fault cost function: if the cost function does not generate a DC component and a second harmonic component, the dual-winding motor is in a healthy state; if the cost function generates a DC component and a second harmonic component, the dual-winding motor is in a phase loss fault state, and the fault index is extracted as the amplitude of the DC component and the second harmonic component generated by the cost function;

[0014] Step 13): Design the fault phase location judgment condition: Detect and obtain the initial phase angle deviation. If the initial phase angle deviation of each winding is equal to 120°, the dual-winding motor is in a healthy state; if the initial phase angle deviation of each winding changes significantly, the dual-winding motor is in a phase-loss fault state, and the initial phase angle deviation index is extracted as the initial phase angle deviation;

[0015] Step 14): Design a fault diagnosis algorithm: If the fault detection flag is detected as 0, the dual-winding motor is in a healthy state and the six-phase fault location flag is 0; if the fault detection flag is detected as 1, the dual-winding motor is in a phase-missing fault state, and the fault location is performed. If the fault location flag of a certain phase is detected as 1 and the fault location flags of the other five phases are 0, then the phase is the fault phase.

[0016] Furthermore, in step 11), when the dual-winding motor is in a healthy state, the dq axis current i d and i q The expression is as follows:

[0017]

[0018] In the formula, i a 、i b 、i c 、i u 、i v 、i w is the six-phase stator current of the double-winding motor; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor.

[0019] Furthermore, in step 11), it is assumed that a phase fails, the dual-winding motor is in a phase-loss fault state, and the dq-axis current i′ of the faulty winding d and i q The expression is as follows:

[0020]

[0021] Where ζ is the amplitude coefficient; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor; θ cf is the angle offset.

[0022] Furthermore, in step 12), the dq axis current i′ of the fault winding d and i′ q The discretized expression is as follows:

[0023]

[0024] In the formula, i′ d(k+2) and i′ q (k+2) is the dq axis current detected at time k+2 under the fault state; i d (k+2) and i q (k+2) is the dq axis current detected at time k+2 in the healthy state; θ e is the electrical angle of the rotor; θ cf is the angle offset.

[0025] Furthermore, the cost function J in step 12) is expressed as follows:

[0026]

[0027] Where Q and R are the weight coefficient matrices of output and control increment respectively; ζ is the amplitude coefficient; θ e is the electrical angle of the rotor; θ cf is the angle offset; I m is the amplitude of the stator current; Δu is the difference between the voltage input at sampling time k and sampling time k-1.

[0028] Furthermore, in step 13), the initial phase angle deviation d of the winding mn The expression is as follows:

[0029]

[0030] In the formula, θ j is the initial phase angle of the basic component of the stator current, j = a, b, c; in a healthy state, d mn =120°; assuming the fault occurs in phase c, then d ab Equal to 180°, d ac and d bc is a variable.

[0031] Furthermore, the fault diagnosis algorithm expression in step 14) is as follows:

[0032]

[0033] In the formula, when the Boolean variable is zero, the value of counter1 is reset to zero. If the counter1 is greater than the constant COUNT1, Flag is set from low to high. Flag and Flag mn are the fault detection flag and fault location flag respectively; counter1 is the count value from the detection of Boolean variable ε = 1 to the constant COUNT1; counter2 is the count value from the detection of Boolean variable ε = 1 to the detection of constant COUNT1; mn =1 detection starts until the count value reaches the constant COUNT2.

[0034] Furthermore, in step 14), the Boolean variables ε, ε mn And the count value expression is as follows:

[0035]

[0036] In the formula, I dc and I2 are the amplitudes of the DC component and the second harmonic component respectively; and is the set threshold; ε and ε mn Boolean type variables for the generated fault indication and phase deviation angle indication respectively;

[0037]

[0038] Where, T s is the sampling period; T is the stator current period; m is the sensitivity factor, COUNT1=m1*T / T s ,COUNT2=m2*T / T s .

[0039] Furthermore, in step 2), a prediction model of a dual-winding motor in a healthy state is established, which specifically includes:

[0040] Step 211): Establish the electrical equation of the rotating coordinate system in a healthy state, the expression is as follows:

[0041]

[0042] In the formula, u d 、u q is the stator voltage in the dq plane; u x 、u y is the stator voltage in the xy plane; i d 、i q is the stator current in the dq plane; i x 、i y is the stator current in the xy plane; L d , L q is the inductance in the dq coordinate system; L ls is the stator leakage inductance; ψ f is the magnetic flux amplitude; R s is the stator resistance; ω e is the electrical angular velocity; ψ d , q is the magnetic flux value in the dq plane; ψ x , y is the magnetic flux value in the xy plane;

[0043] Step 212): Establish a prediction model for a dual-winding motor in a healthy state, and the expression is as follows:

[0044]

[0045] Where i(k) and i(k+1) are the current value at sampling time k and the predicted current value at sampling time k+1 respectively; i d 、i q 、i x 、i y is the state variable and the output variable of the dual-winding steer-by-wire system; y(k) is the current input at sampling time k; is the voltage input at sampling time k; ω e (k) is the electrical angular velocity at time k; ψ f is the flux amplitude; the state update coefficient matrices A, B, and C are expressed as follows:

[0046]

[0047] Where, L d , L q is the inductance in the dq coordinate system; T s is the sampling period; L z is the inductance in the xy coordinate system; R s is the stator resistance.

[0048] Furthermore, the step 2) of reconstructing the prediction model of the dual-winding motor under the phase failure state specifically includes:

[0049] Step 221): reconstructing the voltage equation and flux equation of the natural coordinate system under the phase failure state;

[0050] After one phase of the dual-winding motor is disconnected, the voltage equation and flux equation of the other phases in the natural coordinate system are reconstructed, and the expressions are as follows:

[0051]

[0052] ψ s =L s ·i s +ψ f ·F(θ e )

[0053]

[0054]

[0055] In the formula, u s =[u A u B u C u U u V ] T is the stator voltage matrix; is =[i A i B i C i U i V ] T is the stator current matrix; R n =RI5 is the winding resistance matrix; F(θ e ) is the flux linkage coefficient matrix; ψ s =[ψ A ψ B ψ C ψ U ψ V ] T is the flux matrix of each phase; ψ f is the flux amplitude; I5 is the five-dimensional unit matrix; L1 is the leakage inductance of the stator winding; L m Mainly self-conscious; L s is the stator inductance matrix; θ e is the electrical angle of the rotor;

[0056] Step 222): reconstructing a prediction model of a dual-winding motor under a phase failure state;

[0057] The electrical equations of the harmonic subspace under the synchronously rotating coordinate system are reconstructed as follows:

[0058]

[0059] In the formula, u d ,u q represents the dq axis voltage; i d ,i q represents the dq axis current; u z1 ,u z2 ,u z3 represents the harmonic subspace voltage; i z1 ,i z2 ,i z3 represents the current in the subspace z1, z2, z3; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; V1(θ e ) and W1(θ e ) is the coefficient matrix when one phase is disconnected, and the expression is as follows:

[0060]

[0061] In the formula, θ e is the electrical angle of the rotor;

[0062] Reconstruct the prediction model of the dual-winding motor under the phase loss fault state, the expression is as follows:

[0063]

[0064]

[0065] In the formula, u′ d is the d-axis voltage under the phase failure state, u′ q is the q-axis voltage under the phase failure state, L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; ψ f is the magnetic flux amplitude; ω e is the electrical angular velocity, is the inverse matrix of the coefficient matrix when one phase is disconnected; υ(θ e ) represents the rotor flux offset vector caused by current imbalance in the dq axis coordinate system.

[0066] Furthermore, the step 3) specifically includes:

[0067] Step 31): Solve the model predictive control objective function to obtain the control input voltage of the nominal state

[0068] The model predictive control objective function J is defined as the sum of the absolute value of the current error and the control increment, and the expression is as follows:

[0069]

[0070] In the formula, y p (k+i|k) is the control output prediction value, N c To control the step size, i = 0, 1, ..., N c -1; G and R are the weight coefficient matrices of output and control increment respectively; y ref (k+i|k) is the control output reference value; N p is the prediction step length;

[0071] Set the constraints as:

[0072] u min ≤u(k+i)≤u max ,i=0,1,…,N c -1

[0073] In the formula, u min is the minimum output voltage, u max is the maximum output voltage;

[0074] According to the above model predictive control objective function and constraints, the model predictive control is transformed into an optimization problem that minimizes the model predictive control objective function under the premise of satisfying the constraints. The expression is as follows:

[0075]

[0076] The linear matrix inequality method is used to solve the model predictive control objective function and obtain the voltage control signal at time k. The expression is as follows:

[0077]

[0078] In the formula, u d (k),u q (k) is the stator voltage in the dq plane at time k; u x (k),u y (k) is the stator voltage in the xy plane at time k; the control input voltage of the nominal state at time k is obtained

[0079] Step 32): Obtain the rotor electrical angle θ of the dual-winding motor with a phase failure at time k e (k), Update Tube invariant set;

[0080] The compensation control gain K is designed to make the trajectory of the actual dual-winding motor system in the Tube sequence. The Tube sequence X is centered on the optimal trajectory of the nominal model without disturbance terms, thereby ensuring that the dual-winding motor can converge asymptotically and stably to the Tube invariant set Z. The expression of the Tube sequence X is as follows:

[0081] X:={X1,X2,···,X N}

[0082] In the formula, is the nominal model state;

[0083] From time k onwards, the expression of the Tube invariant set Z at step i is as follows:

[0084]

[0085] Among them, Z(i|k) is the Tube invariant set containing the origin; N c is the control step size; w(i-1|k) is the disturbance of the system at time k+i-1; Z(i-1|k) is the Tube invariant set of the system at time k+i-1; A K is the parameter matrix of the system at time k+i-1, and its expression is as follows:

[0086] A K =A 0 +QK

[0087] In the formula, A 0is the nominal state matrix without considering the change of electrical angle, Q is the control matrix, and the expression is as follows:

[0088]

[0089] In the formula, θ e (k) is the rotor electrical angle at time k; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; T s is the sampling period; R s is the stator resistance;

[0090] Step 33): Use the Tube invariant set Z of the i-th step from the k-th moment obtained in step 32) to update the objective function and constraints, and use the linear matrix inequality method to solve the model predictive control objective function to obtain the control input voltage at the k+i moment;

[0091] The updated objective function and constraints are as follows:

[0092]

[0093] Among them, x ref (i|k) is the reference current, G and R are the weight coefficient matrices of the reference current and the nominal state respectively, P is the weight coefficient matrix of the control input voltage, X m is a terminal constraint and X m ∈X;

[0094] Step 34): Get the actual state of the system x(i|k), and calculate the error between the actual state of the system and the center trajectory of the Tube invariant set Generate auxiliary control input It is superimposed with the control input voltage of the nominal state at time k+i obtained in step 31), and acts together on the dual-winding motor to achieve stability control of the dual-winding motor in a healthy state and a phase-loss fault state;

[0095] The actual input u(i|k) acting on the dual-winding steer-by-wire system is expressed as follows:

[0096]

[0097] Beneficial effects of the present invention:

[0098] The present invention can ensure that the steering motor has fault tolerance when a local failure occurs, so that the wire-controlled steering system can effectively isolate and actively reconstruct the fault point according to the stability condition. At the same time, the accuracy, stability and safety control performance of the steering motor in the case of a local failure is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1 It is a schematic diagram of the process of the present invention;

[0100] Figure 2 This is a flow chart for diagnosing phase loss fault in a dual-winding motor. DETAILED DESCRIPTION

[0101] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0102] Reference Figure 1 As shown, a fault-tolerant control method for a dual-winding wire-controlled steering system based on a prediction model of the present invention comprises the following steps:

[0103] Step 1): Design a phase loss fault diagnosis method, perform fault diagnosis on the dual-winding motor, and obtain the fault diagnosis result; specifically including:

[0104] Step 11): Design the dq axis current judgment condition for phase failure: If the dq axis current i d =0,i q =I m , then the dual-winding motor is in a healthy state; if the dq axis current i′ d ≠0, i q ′≠I m , then the dual-winding motor is in a phase-loss fault state, i d 、i q are the direct axis current and quadrature axis current in the synchronous rotating coordinate system under the healthy state, i′ d 、i q ′ are the direct-axis current and quadrature-axis current in the synchronous rotating coordinate system under the phase failure state, I m is the amplitude of the stator current;

[0105] Step 12): Design the judgment condition of the phase loss fault cost function: if the cost function does not generate a DC component and a second harmonic component, the dual-winding motor is in a healthy state; if the cost function generates a DC component and a second harmonic component, the dual-winding motor is in a phase loss fault state, and the fault index is extracted as the amplitude of the DC component and the second harmonic component generated by the cost function;

[0106] Step 13): Design the fault phase location judgment condition: Detect and obtain the initial phase angle deviation. If the initial phase angle deviation of each winding is equal to 120°, the dual-winding motor is in a healthy state; if the initial phase angle deviation of each winding changes significantly, the dual-winding motor is in a phase-loss fault state, and the initial phase angle deviation index is extracted as the initial phase angle deviation;

[0107] Step 14): Design a fault diagnosis algorithm: If the fault detection flag is detected as 0, the dual-winding motor is in a healthy state and the six-phase fault location flag is 0; if the fault detection flag is detected as 1, the dual-winding motor is in a phase-missing fault state, and the fault location is performed. If the fault location flag of a certain phase is detected as 1 and the fault location flags of the other five phases are 0, then the phase is the fault phase.

[0108] Wherein, when the dual-winding motor is in a healthy state in step 11), the dq axis current i d and i q The expression is as follows:

[0109]

[0110] In the formula, i a 、i b 、i c 、i u 、i v 、i w is the six-phase stator current of the double-winding motor; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor.

[0111] In the step 11), it is assumed that a phase fails, the dual-winding motor is in a phase-loss fault state, and the dq-axis current i′ of the faulty winding d and i q The expression is as follows:

[0112]

[0113] Where ζ is the amplitude coefficient; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor; θ cf is the angle offset.

[0114] Wherein, the dq axis current i of the fault winding in step 12) is d ′ and i q The discretization expression of ′ is as follows:

[0115]

[0116] In the formula, i′ d (k+2) and i′ q (k+2) is the dq axis current detected at time k+2 under the fault state; i d (k+2) and i q (k+2) is the dq axis current detected at time k+2 in the healthy state; θ e is the electrical angle of the rotor; θ cf is the angle offset.

[0117] The cost function J in step 12) is expressed as follows:

[0118]

[0119] Where Q and R are the weight coefficient matrices of output and control increment respectively; ζ is the amplitude coefficient; θ e is the electrical angle of the rotor; θ cf is the angle offset; I m is the amplitude of the stator current; Δu is the difference between the voltage input at sampling time k and sampling time k-1.

[0120] Wherein, the initial phase angle deviation d of the winding in step 13) is mn The expression is as follows:

[0121]

[0122] In the formula, θ j is the initial phase angle of the basic component of the stator current, j = a, b, c; in a healthy state, d mn =120°; assuming the fault occurs in phase c, then d ab Equal to 180°, d ac and d bc is a variable.

[0123] The fault diagnosis algorithm in step 14) is expressed as follows:

[0124]

[0125] In the formula, when the Boolean variable is zero, the value of counter1 is reset to zero. If the counter1 is greater than the constant COUNT1, Flag is set from low to high. Flag and Flag mn are the fault detection flag and fault location flag respectively; counter1 is the count value from the detection of Boolean variable ε = 1 to the constant COUNT1; counter2 is the count value from the detection of Boolean variable ε = 1 to the detection of constant COUNT1; mn =1 detection starts until the count value reaches the constant COUNT2.

[0126] In step 14), the Boolean variables ε, ε mn And the count value expression is as follows:

[0127]

[0128] In the formula, I dc and I2 are the amplitudes of the DC component and the second harmonic component respectively; and is the set threshold; ε and ε mn Boolean type variables for the generated fault indication and phase deviation angle indication respectively;

[0129]

[0130] Where, T s is the sampling period; T is the stator current period; m is the sensitivity factor, COUNT1=m1*T / T s ,COUNT2=m2*T / T s .

[0131] Step 2): judging the health status of the dual-winding motor according to the fault diagnosis result of step 1); if the dual-winding motor is in a healthy state, establishing a prediction model of the dual-winding motor in a healthy state; if the dual-winding motor is in a phase-loss fault state, reconstructing a prediction model of the dual-winding motor in a phase-loss fault state;

[0132] Wherein, the step 2) establishes a prediction model of a dual-winding motor in a healthy state, specifically including:

[0133] Step 211): Establish the electrical equation of the rotating coordinate system in a healthy state, the expression is as follows:

[0134]

[0135] In the formula, u d 、u q is the stator voltage in the dq plane; u x 、u y is the stator voltage in the xy plane; i d 、i q is the stator current in the dq plane; i x 、i y is the stator current in the xy plane; L d , L q is the inductance in the dq coordinate system; L ls is the stator leakage inductance; ψ f is the magnetic flux amplitude; R s is the stator resistance; ω e is the electrical angular velocity; ψ d , q is the magnetic flux value in the dq plane; ψ x , y is the magnetic flux value in the xy plane;

[0136] Step 212): Establish a prediction model for a dual-winding motor in a healthy state, and the expression is as follows:

[0137]

[0138] Where i(k) and i(k+1) are the current value at sampling time k and the predicted current value at sampling time k+1 respectively; i d 、i q 、i x 、i y is the state variable and the output variable of the dual-winding steer-by-wire system; y(k) is the current input at sampling time k; is the voltage input at sampling time k; ω e (k) is the electrical angular velocity at time k; ψ f is the flux amplitude; the state update coefficient matrices A, B, and C are expressed as follows:

[0139]

[0140] Where, L d , L q is the inductance in the dq coordinate system; T s is the sampling period; L z is the inductance in the xy coordinate system; R s is the stator resistance.

[0141] The step 2) of reconstructing the prediction model of the dual-winding motor under the phase failure state specifically includes:

[0142] Step 221): reconstructing the voltage equation and flux equation of the natural coordinate system under the phase failure state;

[0143] After one phase of the dual-winding motor is disconnected, the voltage equation and flux equation of the other phases in the natural coordinate system are reconstructed, and the expressions are as follows:

[0144]

[0145] ψ s =L s ·i s +ψ f ·F(θ e )

[0146]

[0147] In the formula, u s =[u A u B u C u U u V ] T is the stator voltage matrix; i s =[i A i B i C i U i V ]T is the stator current matrix; R n =RI5 is the winding resistance matrix; F(θ e ) is the flux linkage coefficient matrix; ψ s =[ψ A ψ B ψ C ψ U ψ V ] T is the flux matrix of each phase; ψ f is the flux amplitude; I5 is the five-dimensional unit matrix; L1 is the leakage inductance of the stator winding; L m Mainly self-conscious; L s is the stator inductance matrix; θ e is the electrical angle of the rotor;

[0148] Step 222): reconstructing a prediction model of a dual-winding motor under a phase failure state;

[0149] The electrical equations of the harmonic subspace under the synchronously rotating coordinate system are reconstructed as follows:

[0150]

[0151] In the formula, u d ,u q represents the dq axis voltage; i d ,i q represents the dq axis current; u z1 ,u z2 ,u z3 represents the harmonic subspace voltage; i z1 ,i z2 ,i z3 represents the current in the subspace z1, z2, z3; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; V1(θ e ) and W1(θ e ) is the coefficient matrix when one phase is disconnected, and the expression is as follows:

[0152]

[0153] In the formula, θ e is the electrical angle of the rotor;

[0154] Reconstruct the prediction model of the dual-winding motor under the phase loss fault state, the expression is as follows:

[0155]

[0156] In the formula, u′ d is the d-axis voltage under the phase failure state, u′q is the q-axis voltage under the phase failure state, L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; ψ f is the magnetic flux amplitude; ω e is the electrical angular velocity, is the inverse matrix of the coefficient matrix when one phase is disconnected; υ(θ e ) represents the rotor flux offset vector caused by current imbalance in the dq axis coordinate system.

[0157] Step 3): According to the dual-winding motor prediction model in step 2), solve the objective function to obtain the control input voltage of the nominal state; use the actual state of the dual-winding motor and the updated Tube invariant set to update the objective function to solve the control input voltage of the nominal state at time k+i, and generate the auxiliary control input at time k+i; superimpose the control input voltage of the nominal state at time k+i and the auxiliary control input at time k+i to act on the dual-winding motor, so as to achieve stability control of the dual-winding motor in the healthy state and the phase failure state; specifically including:

[0158] Step 31): Solve the model predictive control objective function to obtain the control input voltage of the nominal state

[0159] The model predictive control objective function J is defined as the sum of the absolute value of the current error and the control increment, and the expression is as follows:

[0160]

[0161] In the formula, y p (k+i|k) is the control output prediction value, N c To control the step size, i = 0, 1, ..., N c -1; G and R are the weight coefficient matrices of output and control increment respectively; y ref (k+i|k) is the control output reference value; N p is the prediction step length;

[0162] Set the constraints as:

[0163] u min ≤u(k+i)≤u max ,i=0,1,…,N c -1

[0164] In the formula, u min is the minimum output voltage, u max is the maximum output voltage;

[0165] According to the above model predictive control objective function and constraints, the model predictive control is transformed into an optimization problem that minimizes the model predictive control objective function under the premise of satisfying the constraints. The expression is as follows:

[0166]

[0167] The linear matrix inequality method is used to solve the model predictive control objective function and obtain the voltage control signal at time k. The expression is as follows:

[0168]

[0169] In the formula, u d (k) and u q (k) is the stator voltage in the dq plane at time k; u x (k) and u y (k) is the stator voltage in the xy plane at time k; the control input voltage of the nominal state at time k is obtained

[0170] Step 32): Obtain the rotor electrical angle θ of the dual-winding motor with a phase failure at time k e (k), Update Tube invariant set;

[0171] The compensation control gain K is designed to make the trajectory of the actual dual-winding motor system in the Tube sequence. The Tube sequence X is centered on the optimal trajectory of the nominal model without disturbance terms, thereby ensuring that the dual-winding motor can converge asymptotically and stably to the Tube invariant set Z. The expression of the Tube sequence X is as follows:

[0172] X:={X1,X2,···,X N}

[0173] In the formula, is the nominal model state;

[0174] From time k onwards, the expression of the Tube invariant set Z at step i is as follows:

[0175]

[0176] Among them, Z(i|k) is the Tube invariant set containing the origin; N c is the control step size; w(i-1|k) is the disturbance of the system at time k+i-1; Z(i-1|k) is the Tube invariant set of the system at time k+i-1; A K is the parameter matrix of the system at time k+i-1, and its expression is as follows:

[0177] A K =A 0 +QK

[0178] In the formula, A 0 is the nominal state matrix without considering the change of electrical angle, Q is the control matrix, and the expression is as follows:

[0179]

[0180] In the formula, θ e (k) is the rotor electrical angle at time k; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; T s is the sampling period; R s is the stator resistance;

[0181] Step 33): Use the Tube invariant set Z of the i-th step from the k-th moment obtained in step 32) to update the objective function and constraints, and use the linear matrix inequality method to solve the model predictive control objective function to obtain the control input voltage at the k+i moment;

[0182] The updated objective function and constraints are as follows:

[0183]

[0184] Among them, x ref (i|k) is the reference current, G and R are the weight coefficient matrices of the reference current and the nominal state respectively, P is the weight coefficient matrix of the control input voltage, X m is a terminal constraint and X m ∈X;

[0185] Step 34): Get the actual state of the system x(i|k), and calculate the error between the actual state of the system and the center trajectory of the Tube invariant set Generate auxiliary control input It is superimposed with the control input voltage of the nominal state at time k+i obtained in step 31), and acts together on the dual-winding motor to achieve stability control of the dual-winding motor in a healthy state and a phase-loss fault state;

[0186] The actual input u(i|k) acting on the dual-winding steer-by-wire system is expressed as follows:

[0187]

[0188] The present invention has many specific application paths. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principle of the present invention. These improvements should also be regarded as the protection scope of the present invention.

Claims

1. A fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model, characterized in that: Here are the steps: Step 1): Design a phase-loss fault diagnosis method, perform fault diagnosis on the dual-winding motor, and obtain a fault diagnosis result; Step 2): judging the health status of the dual-winding motor according to the fault diagnosis result of step 1); if the dual-winding motor is in a healthy state, establishing a prediction model of the dual-winding motor in a healthy state; if the dual-winding motor is in a phase-loss fault state, reconstructing a prediction model of the dual-winding motor in a phase-loss fault state; Step 3): According to the dual-winding motor prediction model in step 2), solve the objective function to obtain the control input voltage of the nominal state; use the actual state of the dual-winding motor and the updated Tube invariant set to update the objective function to solve the control input voltage of the nominal state at time k+i, and generate the auxiliary control input at time k+i; superimpose the control input voltage of the nominal state at time k+i and the auxiliary control input at time k+i and act on the dual-winding motor together to achieve stability control of the dual-winding motor in a healthy state and a phase-loss fault state.

2. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 1, characterized in that: The step 1) specifically includes: Step 11): Design the dq axis current judgment condition for phase failure: If the dq axis current i d =0,i q =I m , then the dual-winding motor is in a healthy state; if the dq axis current i′ d ≠0, i q ′≠I m , then the dual-winding motor is in a phase-loss fault state, i d 、i q are the direct axis current and quadrature axis current in the synchronous rotating coordinate system under the healthy state, i′ d 、i q ′ are the direct-axis current and quadrature-axis current in the synchronous rotating coordinate system under the phase failure state, I m is the amplitude of the stator current; Step 12): Design the judgment condition of the phase loss fault cost function: if the cost function does not generate a DC component and a second harmonic component, the dual-winding motor is in a healthy state; if the cost function generates a DC component and a second harmonic component, the dual-winding motor is in a phase loss fault state, and the fault index is extracted as the amplitude of the DC component and the second harmonic component generated by the cost function; Step 13): Design the fault phase location judgment condition: Detect and obtain the initial phase angle deviation. If the initial phase angle deviation of each winding is equal to 120°, the dual-winding motor is in a healthy state; if the initial phase angle deviation of each winding changes significantly, the dual-winding motor is in a phase-loss fault state, and the initial phase angle deviation index is extracted as the initial phase angle deviation; Step 14): Design a fault diagnosis algorithm: If the fault detection flag is detected as 0, the dual-winding motor is in a healthy state and the six-phase fault location flag is 0; if the fault detection flag is detected as 1, the dual-winding motor is in a phase-missing fault state, and the fault location is performed. If the fault location flag of a certain phase is detected as 1 and the fault location flags of the other five phases are 0, then the phase is the fault phase.

3. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 2, characterized in that: When the dual-winding motor is in a healthy state in step 11), the dq axis current i d and i q The expression is as follows: In the formula, i a 、i b 、i c 、i u 、i v 、i w is the six-phase stator current of the double-winding motor; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor.

4. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 2, characterized in that: In the step 11), it is assumed that a phase fails, the dual-winding motor is in a phase-loss fault state, and the dq-axis current i′ of the faulty winding d and i q The expression is as follows: Where ζ is the amplitude coefficient; I m is the amplitude of the stator current; θ e is the electrical angle of the rotor; θ cf is the angle offset.

5. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 2, characterized in that: The dq axis current i′ of the fault winding in step 12) d and i′ q The discretized expression is as follows: In the formula, i′ d (k+2) and i′ q (k+2) is the dq axis current detected at time k+2 under the fault state; i d (k+2) and i q (k+2) is the dq axis current detected at time k+2 in the healthy state; θ e is the electrical angle of the rotor; θ cf is the angle offset.

6. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 2, characterized in that: The cost function J in step 12) is expressed as follows: Where Q and R are the weight coefficient matrices of output and control increment respectively; ζ is the amplitude coefficient; θ e is the electrical angle of the rotor; θ cf is the angle offset; I m is the amplitude of the stator current; Δu is the difference between the voltage input at sampling time k and sampling time k-1.

7. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 2, characterized in that: The fault diagnosis algorithm expression in step 14) is as follows: In the formula, when the Boolean variable is zero, the value of counter1 is reset to zero. If the counter1 is greater than the constant COUNT1, Flag is set from low to high. Flag and Flag mn are the fault detection flag and fault location flag respectively; counter1 is the count value from the detection of Boolean variable ε = 1 to the constant COUNT1; counter2 is the count value from the detection of Boolean variable ε = 1 to the detection of constant COUNT1; mn =1 detection starts until the count value reaches the constant COUNT2.

8. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 7, characterized in that: In step 14), the Boolean variables ε, ε mn And the count value expression is as follows: In the formula, I dc and I2 are the amplitudes of the DC component and the second harmonic component respectively; and is the set threshold; ε and ε mn Boolean type variables for the generated fault indication and phase deviation angle indication respectively; Where, T s is the sampling period; T is the stator current period; m is the sensitivity factor, COUNT1=m1*T / T s ,COUNT2=m2*T / T s .

9. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 1, characterized in that: The step 2) of reconstructing the prediction model of the dual-winding motor under the phase failure state specifically includes: Step 221): reconstructing the voltage equation and flux equation of the natural coordinate system under the phase failure state; After one phase of the dual-winding motor is disconnected, the voltage equation and flux equation of the other phases in the natural coordinate system are reconstructed, and the expressions are as follows: ψ s =L s ·i s +ψ f ·F(θ e ) In the formula, u s =[u A u B u C u U u V ] T is the stator voltage matrix; i s =[i A i B i C i U i V ] T is the stator current matrix; R n =RI5 is the winding resistance matrix; F(θ e ) is the flux linkage coefficient matrix; ψ s =[ψ A ψ B ψ C ψ U ψ V ] T is the flux matrix of each phase; ψ f is the flux amplitude; I5 is the five-dimensional unit matrix; L1 is the leakage inductance of the stator winding; L m Mainly self-conscious; L s is the stator inductance matrix; θ e is the electrical angle of the rotor; Step 222): reconstructing a prediction model of a dual-winding motor under a phase failure state; The electrical equations of the harmonic subspace under the synchronously rotating coordinate system are reconstructed as follows: In the formula, u d ,u q represents the dq axis voltage; i d ,i q represents the dq axis current; u z1 ,u z2 ,u z3 represents the harmonic subspace voltage; i z1 ,i z2 ,i z3 represents the current in the subspace z1, z2, z3; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; V1(θ e ) and W1(θ e ) is the coefficient matrix when one phase is disconnected, and the expression is as follows: In the formula, θ e is the electrical angle of the rotor; Reconstruct the prediction model of the dual-winding motor under the phase loss fault state, the expression is as follows: In the formula, u′ d is the d-axis voltage under the phase failure state, u′ q is the q-axis voltage under the phase failure state, L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; ψ f is the magnetic flux amplitude; ω e is the electrical angular velocity, V1 -1 (θ e ) is the inverse matrix of the coefficient matrix when one phase is disconnected; υ(θ e ) represents the rotor flux offset vector caused by current imbalance in the dq axis coordinate system.

10. The fault-tolerant control method for a dual-winding steer-by-wire system based on a prediction model according to claim 1, characterized in that: The step 3) specifically includes: Step 31): Solve the model predictive control objective function to obtain the control input voltage of the nominal state The model predictive control objective function J is defined as the sum of the absolute value of the current error and the control increment, and the expression is as follows: In the formula, y p (k+i|k) is the control output prediction value, N c To control the step size, i = 0, 1, ..., N c -1; G and R are the weight coefficient matrices of output and control increment respectively; y ref (k+i|k) is the control output reference value; N p is the prediction step length; Set the constraints as: u min ≤u(k+i)≤u max ,i=0,1,…,N c -1 In the formula, u min is the minimum output voltage, u max is the maximum output voltage; According to the above model predictive control objective function and constraints, the model predictive control is transformed into an optimization problem that minimizes the model predictive control objective function under the premise of satisfying the constraints. The expression is as follows: The linear matrix inequality method is used to solve the model predictive control objective function and obtain the voltage control signal at time k. The expression is as follows: In the formula, u d (k) and u q (k) is the stator voltage in the dq plane at time k; u x (k) and u y (k) is the stator voltage in the xy plane at time k; the control input voltage of the nominal state at time k is obtained Step 32): Obtain the rotor electrical angle θ of the dual-winding motor with a phase failure at time k e (k), Update Tube invariant set; The compensation control gain K is designed to make the trajectory of the actual dual-winding motor system in the Tube sequence. The Tube sequence X is centered on the optimal trajectory of the nominal model without disturbance terms, thereby ensuring that the dual-winding motor can converge asymptotically and stably to the Tube invariant set Z. The expression of the Tube sequence X is as follows: X:={X1,X2,···,X N } In the formula, is the nominal model state; From time k onwards, the expression of the Tube invariant set Z at step i is as follows: Among them, Z(i|k) is the Tube invariant set containing the origin; N c is the control step size; w(i-1|k) is the disturbance of the system at time k+i-1; Z(i-1|k) is the Tube invariant set of the system at time k+i-1; A K is the parameter matrix of the system at time k+i-1, and its expression is as follows: A K =A 0 +QK In the formula, A 0 is the nominal state matrix without considering the change of electrical angle, Q is the control matrix, and the expression is as follows: In the formula, θ e (k) is the rotor electrical angle at time k; L d , L q is the inductance in the dq coordinate system; L1 is the leakage inductance of the stator winding; T s is the sampling period; R s is the stator resistance; Step 33): Use the Tube invariant set Z of the i-th step from the k-th moment obtained in step 32) to update the objective function and constraints, and use the linear matrix inequality method to solve the model predictive control objective function to obtain the control input voltage at the k+i moment; The updated objective function and constraints are as follows: Among them, x ref (i|k) is the reference current, G and R are the weight coefficient matrices of the reference current and the nominal state respectively, P is the weight coefficient matrix of the control input voltage, X m is a terminal constraint and X m ∈X; Step 34): Get the actual state of the system x(i|k), and calculate the error between the actual state of the system and the center trajectory of the Tube invariant set Generate auxiliary control input It is superimposed with the control input voltage of the nominal state at time k+i obtained in step 31), and acts together on the dual-winding motor to achieve stability control of the dual-winding motor in a healthy state and a phase-loss fault state; The actual input u(i|k) acting on the dual-winding steer-by-wire system is expressed as follows:

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