Tiny fault detection method for rotary transformer of vehicle driving motor

Abstract

The invention relates to a tiny fault detection method for a rotary transformer of a vehicle driving motor. The method comprises the following steps: acquiring a three-phase current measured value of a motor, a rotating speed measured value of a motor rotor and a position angle measured value; converting the three-phase current measured value of the motor into a fixed coordinate system through coordinates to obtain a two-phase current measured value; obtaining a two-phase current estimated value, a rotating speed estimated value of the motor rotor and a position angle estimated value output by the fault detection observer, comparing the two-phase current estimated value, the rotating speed estimated value of the motor rotor and the position angle estimated value with the two-phase current measured value, the rotating speed measured value of the motor rotor and the position angle measured value, and calculating to obtain an evaluation function value; whether the evaluation function value exceeds a pre-configured threshold value or not is judged, and if yes, it is judged that the rotary transformer has a fault. Compared with the prior art, the method has the advantages that the influence of the fault can be distinguished from the uncertainty and noise of the system, so that the detection precision is improved.

Description

Technical Field

[0001] The invention relates to the technical field of fault diagnosis of vehicle electric drive systems, and in particular to a method for detecting minor faults of a rotary transformer of a vehicle drive motor. Background Art

[0002] Permanent magnet synchronous motors have been widely used in automotive electric drive systems due to their simple structure, high efficiency, and easy control. At present, in the drive control algorithm of automotive permanent magnet synchronous AC motors, a rotary transformer is generally used to detect the motor rotor position and extract speed information, and this information is fed back to the closed-loop control system to ensure the stable operation of the system. However, the external conditions of the rotary transformer of automotive permanent magnet synchronous motors are relatively harsh. In a complex working environment, it is very likely to cause the rotary transformer to fail, making the rotor position and speed fed back to the control system inaccurate, resulting in unstable motor power output, inability to adjust voltage and current in real time, and overall performance degradation. Unfavorable effects, which can easily lead to safety issues such as motor runaway and controller overcurrent. Therefore, the safety and reliability guarantee of permanent magnet synchronous motors is an issue worthy of in-depth exploration.

[0003] The requirements of high safety and reliability make fault detection of permanent magnet synchronous motor an important issue. For the entire control system of permanent magnet synchronous motor, if the fault can be detected quickly and accurately, appropriate measures can be taken in time to deal with it, to a certain extent, avoid accidents and reduce losses. Current fault detection mainly includes model-based and data-based methods. Among them, data-based methods use the existing knowledge base or database of the system to establish fault models through reinforcement learning, machine learning and other methods, but the results lack interpretability and are overly dependent on the database; model-based methods combine the analysis and modeling of system characteristics to diagnose faults through the difference between observed signals and actual signals.

[0004] The model-based method mainly completes the fault detection by designing an observer. However, in the actual application process, the existence of factors such as measurement noise and external interference will affect the performance of the observer-based fault detection method to a certain extent, causing false alarms. In view of the existence of external interference and measurement noise, some scholars have proposed a robust observer with interference suppression, which solves the problem of separating fault signals and interference signals in the presence of unknown interference. However, when a minor fault occurs, the fault signal is easily regarded as an unknown disturbance, which is covered and suppressed, affecting the performance of the fault observer. In order to better distinguish the impact of the fault from the uncertainty and noise of the system, it is necessary to design a robust observer with interference suppression and fault sensitivity. Summary of the invention

[0005] The purpose of the present invention is to provide a method for detecting minor faults of a rotary transformer of a vehicle drive motor.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A method for detecting minor faults of a rotary transformer of a vehicle drive motor, comprising:

[0008] Collect the measured values ​​of the three-phase current of the motor, the measured values ​​of the speed of the motor rotor and the measured values ​​of the position angle;

[0009] The measured values ​​of the three-phase current of the motor are transformed into a fixed coordinate system to obtain the measured values ​​of the two-phase current;

[0010] Obtain the estimated values ​​of the two-phase current, the estimated values ​​of the rotational speed of the motor rotor and the estimated values ​​of the position angle output by the fault detection observer, compare them with the actual measured values ​​of the two-phase current, the actual measured values ​​of the rotational speed of the motor rotor and the actual measured values ​​of the position angle, and calculate the evaluation function value;

[0011] It is determined whether the evaluation function value exceeds a preconfigured threshold value. If yes, it is determined that the resolver is faulty.

[0012] The fault detection observer is designed based on a linear variable parameter model, and the linear variable parameter model is specifically a linear variable parameter model of a permanent magnet synchronous motor in a fixed coordinate system with a tracking error as a state variable.

[0013] The linear variable parameter model is:

[0014]

[0015] y(t)=Cx(t)+Ew(t)+F a f a (t)

[0016] in: is the derivative of the actual state value of the tracking error system, A(δ1,δ2) is the state matrix, x(t) is the actual state value of the tracking error system, B is the input matrix, u(t) is the control input of the system, B d is the interference matrix, d(t) is the external environment interference, y(t) is the actual value of the system output, which is composed of the measured values ​​of the two-phase current, the measured values ​​of the motor rotor speed and the measured values ​​of the position angle, C is the output matrix, E is the noise matrix, w(t) is, F a is the fault matrix, f a (t) is sensor failure.

[0017] The linear variable parameter model is established based on the mechanical characteristics and electrical characteristics of the permanent magnet synchronous motor.

[0018] The mathematical expression of the fault detection observer is:

[0019]

[0020] in: is the derivative of the state estimate of the tracking error system, A(η) is the characteristic matrix of the linear variable parameter model, is the state estimate of the tracking error system, L(η) is the gain of the observer, is the system output estimate, which is composed of the two-phase current estimate, the motor rotor speed estimate and the position angle estimate. r(t) is the residual value of the tracking error system, and V is the residual coefficient weighting matrix.

[0021] The process of determining the gain and residual coefficient weighting matrix of the observer includes:

[0022] Applying performance indicators enhances the sensitivity of residual values ​​to fault signals;

[0023] Application H ∞ The performance index weakens the influence of interference and noise signals on the residual value;

[0024] Analyze the steady-state conditions of the fault detection observer using Lyapunov stability;

[0025] Taking into account the fault sensitivity conditions, disturbance robustness conditions and stability conditions, the gain solution problem of the fault detection observer is transformed into a feasibility problem of linear matrix inequality, and the gain and residual coefficient weighting matrix of the observer are obtained.

[0026] The application performance index enhances the sensitivity of the residual value to the fault signal and satisfies:

[0027]

[0028] The application H ∞ The performance index weakens the influence of interference and noise signals on the residual value and satisfies:

[0029]

[0030] Among them, γ is the interference suppression gain index, and β is the fault sensitivity coefficient index.

[0031] The process of obtaining the evaluation function value includes:

[0032] According to the two-phase current estimation value, the motor rotor speed estimation value and the position angle estimation value output by the tracking error system, the differences with the respective measured values ​​are calculated as the difference values ​​of the two-phase current, the motor rotor speed and the position angle;

[0033] The weighted error value is calculated using the residual coefficient weighting matrix, and the evaluation function value is calculated in combination with the weighted residual value:

[0034]

[0035] Where: J(t) is the evaluation function value.

[0036] The state error of the tracking error system is:

[0037]

[0038] Where: e(t) is the state error, D e is the aggregate interference input matrix, D w is the aggregate interference output matrix, is the lumped disturbance variable.

[0039] The motor is a permanent magnet synchronous motor.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. Using the constructed observer, the two-phase current estimation value, the motor rotor speed estimation value and the position angle estimation value are compared with the corresponding measured values ​​to determine whether there is a minor fault, which has the advantage of high efficiency.

[0042] 2. When solving the observer gain, the fault sensitivity index H is used - , interference robustness index H ∞ The stability conditions not only reduce the impact of external interference and noise on fault detection, but also enhance the sensitivity of the residual signal to fault information, so that the residual signal changes drastically at the moment of fault occurrence, reducing the false alarm rate and improving the accuracy of permanent magnet synchronous motor position sensor fault detection. In addition, the fault detection structure is simple, and there is no need to design a multi-channel observer. Only a unified fault detection observer and a residual coefficient matrix need to be designed to generate a weighted residual signal to complete the fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the physical model of permanent magnet synchronous motor;

[0044] Figure 2 This is a flow chart of transformer minor fault detection according to the present invention;

[0045] Figure 3 The dynamic threshold and state evaluation function curve of the permanent magnet synchronous motor rotary transformer in the present invention when a minor fault (10 degree electrical angle error) occurs and when no fault occurs;

[0046] Figure 4The residual signal comparison curves of the permanent magnet synchronous motor rotary transformer in the present invention when a minor fault (10 degree electrical angle error) occurs and when no fault occurs, wherein (a) is the angular velocity error observation residual comparison diagram, and (b) is the αβ axis current error observation residual comparison diagram. DETAILED DESCRIPTION

[0047] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0048] A method for detecting minor faults of a rotary transformer of a vehicle drive motor. Figure 2 As shown, including:

[0049] Collect the measured values ​​of the three-phase current of the motor, the measured values ​​of the speed of the motor rotor, and the measured values ​​of the position angle, wherein the motor is specifically a permanent magnet synchronous motor, such as Figure 2 As shown,

[0050] The measured values ​​of the three-phase current of the motor are transformed into a fixed coordinate system to obtain the measured values ​​of the two-phase current;

[0051] Obtain the estimated values ​​of the two-phase current, the estimated values ​​of the rotational speed of the motor rotor and the estimated values ​​of the position angle output by the fault detection observer, compare them with the actual measured values ​​of the two-phase current, the actual measured values ​​of the rotational speed of the motor rotor and the actual measured values ​​of the position angle, and calculate the evaluation function value;

[0052] It is determined whether the evaluation function value exceeds a preconfigured threshold value. If yes, it is determined that the resolver is faulty.

[0053] Among them, the fault detection observer is designed based on the linear variable parameter model, and the linear variable parameter model is specifically a linear variable parameter model of the permanent magnet synchronous motor with tracking error as the state variable in a fixed coordinate system.

[0054] Specifically, the mechanical and electrical characteristics of the permanent magnet synchronous motor are analyzed, and the state equations of the mechanical and electrical parts established in the stationary coordinate system are:

[0055]

[0056] Among them, ω m is the mechanical angular velocity of the motor rotor, J m is the moment of inertia of the rotor, B ω is the viscous drag coefficient, T L is the load torque of the motor, T e is the electromagnetic torque of the motor, p n is the number of rotor pole pairs, R s is the stator resistance, uα ,u β are the components of the stator voltage on the α-β axis, i α ,i β are the components of the stator current on the α-β axis, ψ f is the permanent magnet flux, L S is the stator winding inductance.

[0057] The systematic error is defined as follows:

[0058] e α =i α * -i α ,e β =i β * -i β

[0059] Then the system dynamic tracking error can be expressed as:

[0060]

[0061] Use the following nonlinear matrix modulation and redefine the voltage input:

[0062]

[0063] Among them, u in_α and u in_β is the state feedback controller input, rewriting the dynamic error to obtain:

[0064]

[0065] The state variables and control inputs are set as u=[u in_α ,u in_β ] T , and define the parameters as

[0066] δ1(θ m )=p n ψ f sin(p n θ m )

[0067] δ2(θ m )=p n ψ f cos(p n θ m )

[0068] Because the nonlinear term is a bounded trigonometric function, and δ1(θ m ) and δ2(θm ) has the following boundaries:

[0069]

[0070] Therefore, the linear variable parameter model can be obtained as:

[0071]

[0072] y(t)=Cx(t)+Ew(t)+F a f a (t)

[0073] in: is the derivative of the actual state value of the tracking error system, A(δ1,δ2) is the state matrix, x(t) is the actual state value of the tracking error system, B is the input matrix, u(t) is the control input of the system, B d is the interference matrix, d(t) is the external environment interference, y(t) is the actual value of the system output, which is composed of the measured values ​​of the two-phase current, the measured values ​​of the motor rotor speed and the measured values ​​of the position angle, C is the output matrix, E is the noise matrix, w(t) is, F a is the fault matrix, f a (t) is the sensor failure, where d = [d1 d2 d2 d3] T .

[0074] It is linearized and converted into a linear variable parameter model. Considering δ1(θ m ),δ2(θ m ) is bounded, and the premise variable is selected as ρ = [δ1, δ2], and the linear variable parameter model of the permanent magnet synchronous motor system tracking error is obtained as follows:

[0075]

[0076] y(t)=Cx(t)+Ew(t)+F a f a (t)

[0077] where η i (ρ) is the membership function, and In this embodiment, the specific form is as follows:

[0078]

[0079] Specifically, based on the established linear variable parameter model of permanent magnet synchronous motor system tracking error, the fault detection observer is established as

[0080]

[0081] in: is the derivative of the state estimate of the tracking error system, A(η) is the characteristic matrix of the linear variable parameter model, is the state estimate of the tracking error system, L(η) is the gain of the observer, is the system output estimate, which is composed of the two-phase current estimate, the motor rotor speed estimate and the position angle estimate. r(t) is the residual value of the tracking error system, and V is the residual coefficient weighting matrix.

[0082] Defining new aggregate interference Defining state error After sorting, the system state error dynamics can be obtained as follows:

[0083]

[0084] Among them A C (η)=A(η)-L(η)C,D e =[B d 0],D w =[0E].

[0085] Performance indicators of fault detection observer: Application H - The performance index enhances the sensitivity of the residual value to the fault signal, making Application H ∞ The performance index weakens the influence of interference and noise signals on the residual value, making The steady-state conditions of the fault detection observer are analyzed using Lyapunov stability. Taking into account the fault sensitivity conditions, disturbance robustness conditions and stability conditions, the gain solution problem of the fault detection observer is transformed into a feasibility problem of linear matrix inequality, and the observer gain L(η) and the residual coefficient weighting matrix V are obtained with the help of the matrix toolbox.

[0086] In addition, specifically, according to the known conditions related to noise and external interference, the dynamic threshold R for detecting faults is calculated and set. th =f(||d|| ∞ ,||w|| ∞ ,t), where ||·|| ∞ represents the ∞ norm of a vector, R th is a function related to interference d, noise w and time t. Set the state evaluation function related to the residual signal to According to the measured output of the permanent magnet synchronous motor tracking error system state and the observed output of the fault detection observer, the residual values ​​with the four state variables are calculated, the weighted error value is calculated using the residual coefficient weighted matrix obtained by solving, and the state evaluation function J(t) is calculated in combination with the weighted residual value.

[0087] The obtained state evaluation function value is compared with the set dynamic threshold. If the value of the state evaluation function J(t) exceeds the set dynamic threshold R th , that is, J(t)>R th , it is determined that the permanent magnet synchronous motor operation system has a fault. Figure 3 and Figure 4 As shown in Figure 2, at the beginning of the system operation, the evaluation function value increases rapidly, but at this stage the dynamic threshold R th It is also relatively large, which prevents the system from false alarms. During the stable operation stage of the system, the dynamic threshold also tends to be stable. At this time, after the fault signal is added at 2.5 seconds, the residual evaluation function value quickly exceeds the set dynamic threshold, indicating that after the fault occurs, the method in the present invention successfully and quickly detects the sensor fault.

[0088] The above simulation experiments verify the accuracy and rapidity of the permanent magnet synchronous motor position sensor fault detection method of the present invention.

[0089] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

Claims

1. A method for detecting minor faults of a rotary transformer of a vehicle drive motor, characterized in that: include: Collect the measured values ​​of the three-phase current of the motor, the measured values ​​of the speed of the motor rotor and the measured values ​​of the position angle; The measured values ​​of the three-phase current of the motor are transformed into a fixed coordinate system to obtain the measured values ​​of the two-phase current; Obtain the estimated values ​​of the two-phase current, the estimated values ​​of the rotational speed of the motor rotor and the estimated values ​​of the position angle output by the fault detection observer, compare them with the actual measured values ​​of the two-phase current, the actual measured values ​​of the rotational speed of the motor rotor and the actual measured values ​​of the position angle, and calculate the evaluation function value; It is determined whether the evaluation function value exceeds a preconfigured threshold value. If yes, it is determined that the resolver is faulty.

2. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 1, characterized in that: The fault detection observer is designed based on a linear variable parameter model, and the linear variable parameter model is specifically a linear variable parameter model of a permanent magnet synchronous motor in a fixed coordinate system with a tracking error as a state variable.

3. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 2, characterized in that: The linear variable parameter model is: y(t)=Cx(t)+Ew(t)+F a f a (t) in: is the derivative of the actual state value of the tracking error system, A(δ1,δ2) is the state matrix, x(t) is the actual state value of the tracking error system, B is the input matrix, u(t) is the control input of the system, B d is the interference matrix, d(t) is the external environment interference, y(t) is the actual value of the system output, which is composed of the measured values ​​of the two-phase current, the measured values ​​of the motor rotor speed and the measured values ​​of the position angle, C is the output matrix, E is the noise matrix, w(t) is, F a is the fault matrix, f a (t) is sensor failure.

4. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 3, characterized in that: The linear variable parameter model is established based on the mechanical characteristics and electrical characteristics of the permanent magnet synchronous motor.

5. The method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 3, characterized in that: The mathematical expression of the fault detection observer is: in: is the derivative of the state estimate of the tracking error system, A(η) is the characteristic matrix of the linear variable parameter model, is the state estimate of the tracking error system, L(η) is the gain of the observer, is the system output estimate, which is composed of the two-phase current estimate, the motor rotor speed estimate and the position angle estimate. r(t) is the residual value of the tracking error system, and V is the residual coefficient weighting matrix.

6. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 5, characterized in that: The process of determining the gain and residual coefficient weighting matrix of the observer includes: Applying performance indicators enhances the sensitivity of residual values ​​to fault signals; Application H ∞ The performance index weakens the influence of interference and noise signals on the residual value; Analyze the steady-state conditions of the fault detection observer using Lyapunov stability; Taking into account the fault sensitivity conditions, disturbance robustness conditions and stability conditions, the gain solution problem of the fault detection observer is transformed into a feasibility problem of linear matrix inequality, and the gain and residual coefficient weighting matrix of the observer are obtained.

7. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 6, characterized in that: The application performance index enhances the sensitivity of the residual value to the fault signal and satisfies: The application H ∞ The performance index weakens the influence of interference and noise signals on the residual value and satisfies: Among them, γ is the interference suppression gain index, and β is the fault sensitivity coefficient index.

8. The method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 6, characterized in that: The process of obtaining the evaluation function value includes: According to the two-phase current estimation value, the motor rotor speed estimation value and the position angle estimation value output by the tracking error system, the differences with the respective measured values ​​are calculated as the difference values ​​of the two-phase current, the motor rotor speed and the position angle; The weighted error value is calculated using the residual coefficient weighting matrix, and the evaluation function value is calculated in combination with the weighted residual value: Where: J(t) is the evaluation function value.

9. A method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 7, characterized in that: The state error of the tracking error system is: Where: e(t) is the state error, D e is the aggregate interference input matrix, D w is the aggregate interference output matrix, is the lumped disturbance variable.

10. The method for detecting minor faults of a rotary transformer of a vehicle drive motor according to claim 1, characterized in that: The motor is a permanent magnet synchronous motor.

Images