Motor rotary transformer fault detection method and device, electronic equipment and medium

Abstract

The invention provides a motor rotary transformer fault detection method and device, electronic equipment and a medium. The method comprises the following steps: acquiring a phase locking difference value sequence of a motor; the phase locking difference value sequence comprises rotor filtering error values of the motor at a plurality of continuous acquisition moments; wherein each rotor filtering error value is obtained according to the rotor error value of the motor and the rotating speed of the motor at the corresponding acquisition moment, and each rotor error value indicates the difference value between the actual rotor angle value of the motor and the estimated rotor angle value of the motor at the corresponding acquisition moment; identifying a plurality of rotor filtering error values in the phase locking difference value sequence to determine whether a continuous difference value abnormity rule is triggered or not; and if the continuous difference value abnormity rule is triggered, whether the motor has a rotary transformer fault is identified according to the rotor filtering error value corresponding to each sampling moment in the preset time length. According to the invention, through a dual verification mechanism, accurate detection of the motor resolver fault is realized.

Description

Technical Field

[0001] The present application relates to the technical field of motor fault diagnosis, and more specifically, to a motor resolver fault detection method, device, electronic equipment, and medium method. Background Art

[0002] In motor control systems, the angular deviation between the actual and estimated rotor positions is a key indicator for measuring resolver decoding accuracy and control system stability. Traditional phase-locked error detection methods typically use a fixed threshold and static filtering to determine the phase-locked error, with fault triggering based solely on a single over-limit judgment.

[0003] However, the operating conditions of motors are complex and changeable, and the speed may fluctuate violently due to sudden factors such as road conditions and loads, thereby generating a large amount of transient interference. The judgment of a single over-limit is too mechanical and one-sided, and does not comprehensively consider the error fluctuation law under transient interference. It is very easy to misjudge instantaneous fluctuations within the normal range as faults, resulting in frequent misjudgments. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a motor resolver fault detection method, device, electronic equipment and medium, aiming to achieve accurate detection of motor resolver faults.

[0005] In a first aspect, the present application provides a method for detecting a motor resolver fault, the method comprising: obtaining a phase-locked difference sequence of a motor; the phase-locked difference sequence comprising rotor filter error values of the motor at a plurality of consecutive acquisition moments; wherein each rotor filter error value is obtained based on the rotor error value of the motor and the rotational speed of the motor at a corresponding acquisition moment, and each rotor error value indicates the difference between the actual rotor angle value of the motor and the estimated rotor angle value of the motor at a corresponding acquisition moment; identifying multiple rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference exception rule is triggered; if the continuous difference exception rule is triggered, identifying whether the motor has a resolver fault based on the rotor filter error value corresponding to each sampling moment within a preset time length.

[0006] In one possible implementation, multiple rotor filter error values in the phase-locked difference sequence are identified in the following manner: for each rotor filter error value at an acquisition moment in the phase-locked difference sequence, determine whether the rotor filter error value at the acquisition moment is greater than a preset threshold corresponding to the acquisition moment; if the rotor filter error value is greater than the corresponding preset threshold, write the rotor filter error value into the first exception queue.

[0007] In one possible embodiment, whether the continuous difference exception rule is triggered is determined in the following manner: the collection moments corresponding to each rotor filter error value in the first exception queue are extracted; the extracted collection moments are continuity identified, so that when it is identified that there are a predetermined number of rotor filter error values with continuous collection moments in the first exception queue, it is determined that the continuous difference exception rule is triggered, and the collection moment with the closest collection moment among all the predetermined number of rotor filter error values with continuous collection moments in the first exception queue is determined as the primary trigger moment.

[0008] In one possible implementation, whether the motor has a resolver fault is identified in the following manner: a secondary phase-locked difference value sequence of the motor is obtained; the secondary phase-locked difference value sequence includes rotor filter error values of the motor at multiple consecutive acquisition moments within a preset time length, and the preset time length indicates the time length from the primary trigger moment to a preset end moment; for the rotor filter error value at each acquisition moment in the secondary phase-locked difference value sequence, it is determined whether the rotor filter error value at the acquisition moment is greater than a preset threshold value corresponding to the acquisition moment; if the rotor filter error value is greater than the preset threshold value, the rotor filter error value is written into a second abnormal queue; if the ratio between the total number of rotor filter error values in the second abnormal queue and the total number of rotor filter error values in the secondary phase-locked difference value sequence is higher than a warning ratio, it is determined that the motor has a resolver fault.

[0009] In one possible embodiment, the preset threshold corresponding to each acquisition moment is obtained in the following manner: a motor parameter data set corresponding to each preset acquisition duration of the motor is obtained, and a temperature change value and a vibration energy change value of the motor within each preset acquisition duration are obtained; wherein the motor parameter data set includes the motor operating parameters of the motor at each sampling moment within the corresponding preset acquisition duration; for each preset acquisition duration, the motor parameter data set of the preset acquisition duration is input into the prediction model to obtain a basic threshold corresponding to the preset acquisition duration; for each preset acquisition duration, the basic threshold corresponding to the preset acquisition duration is corrected according to the temperature change value and vibration energy change value of the motor within the preset acquisition duration to obtain the preset threshold corresponding to each sampling moment in the preset acquisition duration.

[0010] In one possible embodiment, the method further includes: when the vehicle is in a first operating condition, obtaining a limiting torque value based on the requested torque value and the real-time acceleration change rate of the motor to control the motor to operate according to the limiting torque value, wherein when it is detected that the speed change rate of the motor, the throttle opening of the vehicle and the Z-axis acceleration peak of the vehicle all exceed corresponding warning thresholds, it is determined that the vehicle is in the first operating condition.

[0011] In one possible implementation, the method further includes: when the vehicle is in a second operating condition, obtaining a speed estimation value based on the phase voltage and phase current of the motor to control the motor to operate according to the speed estimation value, wherein when it is detected that the vibration spectrum of the vehicle, the wheel speed difference of the vehicle, and the brake pressure value of the vehicle all exceed corresponding warning thresholds, it is determined that the vehicle is in the second operating condition.

[0012] In a second aspect, the present application provides a motor resolver fault detection device, the device comprising: an acquisition module for acquiring a phase-locked difference sequence of the motor; the phase-locked difference sequence comprises the rotor filter error values of the motor at a plurality of consecutive acquisition moments; wherein each rotor filter error value is obtained based on the rotor error value of the motor and the rotational speed of the motor at a corresponding acquisition moment, and each rotor error value indicates the difference between the actual rotor angle value of the motor and the estimated rotor angle value of the motor at a corresponding acquisition moment; a first identification module for identifying the plurality of rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference abnormality rule is triggered; a second identification module for identifying whether the motor has a resolver fault based on the rotor filter error value corresponding to each sampling moment within a preset time length if the continuous difference abnormality rule is triggered.

[0013] In a third aspect, the present application also provides an electronic device comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the above method are performed.

[0014] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0015] The beneficial effects of the motor resolver fault detection solution of this application are as follows: This application generates corresponding rotor filter error values through the real-time motor's rotor error value and real-time speed at each acquisition moment, effectively suppressing the error fluctuations caused by motor speed fluctuations, and realizing accurate monitoring of motor rotary transformer faults through a dual abnormality mechanism.

[0016] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A flow chart of a motor resolver fault detection method provided in an embodiment of the present application; Figure 2 A flowchart of obtaining a preset threshold corresponding to each acquisition moment provided in an embodiment of the present application; Figure 3 A flowchart of determining a rule for triggering a continuous difference anomaly provided in an embodiment of the present application; Figure 4 A flowchart for identifying a resolver fault in a motor provided by an embodiment of the present application; Figure 5 A schematic diagram of the structure of a motor resolver fault detection device provided in an embodiment of the present application; Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work falls within the scope of protection of the present application.

[0020] First, the application scenarios to which this application is applicable are introduced. This application can be applied to motor fault diagnosis.

[0021] Research has found that in motor control systems, the angular deviation between the actual rotor position and the estimated rotor position is the core indicator for measuring the accuracy of resolver decoding and the stability of the control system. Traditional phase-locked error detection methods usually use fixed thresholds and static filtering (such as first-order inertial filtering, setting a fixed coefficient k=0.05) to judge the phase-locked error, and the fault trigger is only based on a single over-limit judgment. However, this method has obvious defects. On the one hand, due to the failure to consider the transient interference caused by the sharp fluctuation of the speed, the fixed threshold and filtering parameters are difficult to adapt to the dynamic working conditions, which can easily lead to misjudgment. On the other hand, static filtering will cause the error signal to lag when the motor acceleration suddenly changes, and it is impossible to capture the real fault information in a timely and accurate manner. In addition, the error fluctuation law under transient interference is not comprehensively considered, which is extremely dangerous. Momentary fluctuations within the normal range are easily misinterpreted as faults, leading to frequent misjudgments. Furthermore, the strategy for handling special operating conditions, which employs a unified control strategy for all conditions (such as global torque limiting or directly disabling diagnostic functions), also has significant drawbacks. The control strategy is overly conservative, particularly when braking on gravel roads, where diagnostic functions are directly disabled, lacking the ability to detect actual faults. Furthermore, the control method is relatively rigid, employing a fixed torque limit slope (e.g., 1000 Nm / s) under full throttle conditions, which can result in delayed power response or insufficient restriction. Regarding control performance, when the error exceeds 0.02°, motor torque fluctuations may exceed 5%, exacerbating vehicle jitter. If the error exceeds 0.05°, the field weakening control becomes inaccurate, resulting in a 10%-15% reduction in motor efficiency. Furthermore, persistently large errors can trigger overcurrent protection and even pose safety risks, such as electric vehicle stalls and industrial motor runaways.

[0022] Based on this, the embodiments of the present application provide a method, device, electronic equipment and medium for detecting motor resolver faults, which achieve accurate detection of motor resolver faults.

[0023] See also Figure 1 , Figure 1 This is a flow chart of a motor resolver fault detection method provided in an embodiment of the present application. Figure 1 As shown in , the motor resolver fault detection method provided by the embodiment of the present application includes: S101: Obtain a phase-locked difference sequence of a motor.

[0024] Among them, the phase-locked difference value sequence includes the rotor filter error values of the motor at multiple consecutive acquisition moments; wherein, each rotor filter error value is obtained based on the rotor error value and the speed of the motor at a corresponding acquisition moment, and each rotor error value indicates the difference between the actual rotor angle value of the motor and the estimated rotor angle value of the motor at a corresponding acquisition moment, and the sampling period is preferably 1ms.

[0025] As an example, the hardware modules and software algorithms of this solution mainly include: a resolver signal acquisition module, a speed estimation module, a phase-locked error processing unit, and a working condition recognition module.

[0026] The resolver signal acquisition module uses an AD2S1210 decoding chip, configured with a 16-bit resolution and a 10kHz sampling frequency, and outputs the actual rotor angle value θ_actual in real time. The speed estimation module constructs a motor mathematical model based on the extended Kalman filter. After inputting the three-phase current (I_abc), the DC bus voltage (U_dc), and the motor temperature (T_m), it outputs the estimated angle value θ_estimate.

[0027] The phase-locked error processing unit includes an error calculator, a dynamic filter, and a threshold calibrator. The error calculator is used to convert the rotor error value Δθ = |θ_actual - θ_estimate| × (180 / π) into degrees. The dynamic filter is used to perform a variable parameter first-order inertial filtering algorithm on the rotor error value to obtain the rotor filtered error value. The threshold calibrator is used to calculate the preset threshold, and the range of the preset threshold is [0.012°, 0.016°].

[0028] The working condition recognition module is used to recognize the working conditions of the vehicle, including an acceleration detection unit and a road surface recognition unit. The acceleration detection unit calculates the speed change rate α = dω / dt through differential calculation with a 1ms sampling period. The road surface recognition unit performs FFT analysis on the wheel speed sensor signal and extracts the frequency domain characteristics of the vibration component with a frequency range of 5 - 15Hz.

[0029] Specifically, each rotor filtered error value is obtained based on the rotor error value of the motor and the speed of the motor at a corresponding acquisition moment. That is, the rotor error value is dynamically filtered through a dynamic filtering algorithm to obtain the rotor filtered error value. The dynamic filtering algorithm of this application uses an improved first-order inertial filtering algorithm, which can be calculated through the following core formula:

[0030] Where the input is the rotor error value Xn = Δθ from the error calculator, and the output is the filtered rotor filtered error value Yn = Δθ ,

[0030] , the algorithm parameter k value has a dynamic adjustment characteristic (adjustment range 0.01 < k < 0.12). This characteristic directly determines the response speed and noise suppression ability of the filter. To achieve the adjustability of the k value, this application introduces a dynamic parameter adjustment mechanism, that is, the k value is adjusted in real time according to the speed change rate Δω of the motor. The specific strategy is:

[0031] Specifically, k base is the base coefficient, k base=0.05, Δω is the speed change rate, and the sigmoid function can be used to achieve smooth transition adjustment of parameters. The formula of the sigmoid function is:

[0032] At the same time, this application also formulates dynamic response rules, specifically: under low-speed stable operating conditions (|Δω|<3000rpm / s), k≈0.05, focusing on strong noise suppression (attenuation rate>90%) to avoid false triggering; under high-speed transient conditions (|Δω|>5000rpm / s), the k value is increased to the range of 0.08∼0.12, focusing on fast response (delay<5ms) to ensure that real faults are captured in a timely manner.

[0033] As an example, the following table compares the dynamic filtering of this application with traditional static filtering.

[0034]

[0035] As an example, the dynamic filtering algorithm in this application can attenuate transient interference (duration <100ms) by >90% and maintain a steady-state error tracking delay of <5ms. This dynamic filtering algorithm achieves an adaptive balance between noise suppression and signal fidelity. In terms of transient interference suppression, it attenuates short-duration noise (<100ms) by over 90%. Interference such as mechanical vibration noise generated when a vehicle passes over a speed bump is effectively filtered out, preventing false triggering caused by noise interference. In real-world fault monitoring, when the speed fluctuates dramatically (such as braking on gravel roads), the algorithm increases the k value, enabling the filter to quickly track the actual error. For example, a sudden offset (>0.02°) of the resolver encoder can be accurately identified within 10ms. The algorithm utilizes a sigmoid function to achieve a smooth transition in the k value, mitigating the risk of control oscillation caused by sudden parameter changes. Its core mechanism relies on real-time sensing of the speed change rate (Δω) and nonlinearly adjusts the filter coefficient k based on this value, achieving an intelligent trade-off between noise suppression and signal fidelity. This approach maintains high real-time responsiveness even under extreme operating conditions, reducing the overall system false positive rate by over 82%.

[0036] S102: Identify multiple rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference abnormality rule is triggered.

[0037] In a preferred example of the present application, multiple rotor filter error values in the phase-locked difference sequence can be identified by: For the rotor filter error value at each acquisition moment in the phase-locked difference sequence, determine whether the rotor filter error value at the acquisition moment is greater than the preset threshold corresponding to the acquisition moment; if the rotor filter error value is greater than the corresponding preset threshold, write the rotor filter error value into the first exception queue.

[0038] Among them, the present application calibrates corresponding preset thresholds for different collection moments to improve the accuracy of the detection scheme of the present application.

[0039] Below through Figure 2 This section describes the specific process of obtaining the preset threshold corresponding to each collection moment.

[0040] Figure 2 A flowchart for obtaining the preset threshold corresponding to each collection moment provided in an embodiment of the present application.

[0041] S201 , obtaining a motor parameter data set corresponding to each preset acquisition time length of the motor, and obtaining a temperature change value and a vibration energy change value of the motor within each preset acquisition time length.

[0042] Here, the motor parameter data set includes the motor operating parameters of the motor at each sampling moment within a corresponding preset acquisition time period.

[0043] As an example, during the experimental design phase, the dynamic thresholds of this application comprehensively covered typical and extreme conditions. Ten typical road types (such as asphalt roads, cement roads, gravel roads, speed bumps, and icy and snowy roads) and five motor load types (no load, 25% load, 50% load, 75% load, and peak load) were selected for combined testing. At the same time, verification was conducted in extreme environments such as high temperature (80°C), low temperature (-30°C), and high humidity (95% RH). The collected motor operating parameters are shown in the following table:

[0044] In terms of labeling rules, real faults are simulated by artificially injecting resolver signal offset (0.02°~0.05°), and interference samples are constructed using simulated signals such as electromagnetic pulses and mechanical shocks.

[0045] S202 : For each preset acquisition time, input the motor parameter data set of the preset acquisition time into a prediction model to obtain a basic threshold corresponding to the preset acquisition time.

[0046] Specifically, the prediction model of the present application uses Gaussian Process Regression (GPR) combined with multi-sensor data fusion to achieve real-time optimization and adjustment of preset thresholds.

[0047] Specifically, the input of the GPR model is shown in the following table:

[0048] The output target of the GPR model is the basic threshold y=Δθ threshold (Range 0.012°~0.016°).

[0049] As an example, the composite kernel function k(Xi,Xj) is selected to improve the expression ability of the GPR model. The specific formula is:

[0050] Among them, k SE is the square exponential kernel, which is used to capture the nonlinear relationship between speed and vibration. SE The specific formula is:

[0051] Where l is the length scale l, which is 0.5. Lin is a linear kernel used to model the linear effects of temperature and humidity, k Lin The specific formula is:

[0052] Where σ² is the variance and is set to 0.1. Periodic is a periodic kernel used to capture the periodic vibration characteristics of the motor, k Periodic The specific formula is:

[0053] Where P is the period, which is 0.2, l p is the length scale, which is 0.1.

[0054] In the dynamic adjustment stage, 100ms is used as the preset acquisition time. The motor operating parameter data is collected every 100ms and integrated into the motor parameter data set corresponding to the preset acquisition time. After normalization, it is input into the GPR model to output the basic threshold corresponding to the preset acquisition time. The basic threshold is calculated using the following formula:

[0055] Where μ(X) is the GPR predicted mean.

[0056] S203. For each preset acquisition time, according to the temperature change value and vibration energy change value of the motor within the preset acquisition time, correct the basic threshold value corresponding to the preset acquisition time to obtain the preset threshold value corresponding to each sampling moment in the preset acquisition time.

[0057] The preset threshold Threshold is also corrected by two real-time compensation terms. The specific formula is:

[0058] Among them, ΔT is the temperature compensation term, ΔV is the vibration correction term, and the calculation formula of the temperature compensation term is:

[0059] The threshold increases by 0.001° for every 1°C increase in temperature to compensate for resolver signal drift caused by thermal expansion. The vibration correction term is calculated as:

[0060] Specifically, for every 10-fold increase in vibration energy, the threshold is increased by 0.002° to offset the error fluctuation caused by mechanical vibration, and ultimately the dynamic threshold is limited to the boundary range of 0.012°~0.016° to prevent overshoot.

[0061] Below through Figure 3 This section describes the specific process of determining the triggering rules for continuous difference anomalies.

[0062] Figure 3 A flowchart for determining triggering continuous difference anomaly rules provided in an embodiment of the present application.

[0063] S301 : Extracting the collection time corresponding to each rotor filter error value in the first abnormal queue.

[0064] S302. Continuity identification is performed on the extracted acquisition moments, so as to determine the triggering of the continuous difference exception rule when it is identified that there are a predetermined number of rotor filter error values with consecutive acquisition moments in the first exception queue, and determine the acquisition moment closest to the acquisition moment among all the predetermined number of rotor filter error values with consecutive acquisition moments in the first exception queue as the primary trigger moment.

[0065] As an example, it can be set that if there are five consecutive rotor filter error values exceeding the corresponding preset threshold, the continuous difference abnormality rule is triggered, and the collection time corresponding to the last rotor filter error value is determined as the primary trigger time.

[0066] return Figure 1 S103: If the continuous difference abnormality rule is triggered, identify whether the motor has a resolver fault based on the rotor filter error value corresponding to each sampling moment within the preset time length.

[0067] Below through Figure 4 This section describes the specific process of identifying whether a motor has a resolver fault.

[0068] Figure 4 This is a flowchart for identifying a resolver fault in a motor provided by an embodiment of the present application.

[0069] S401: Acquire a secondary phase-locked difference sequence of the motor.

[0070] The secondary phase-locked difference value sequence includes rotor filter error values of the motor at a plurality of consecutive acquisition moments within a preset time length, where the preset time length indicates the time length from the primary trigger moment to the preset end moment.

[0071] Here, the preset time length may be set to 200 ms, that is, the rotor filter error value at each sampling moment within 200 ms is obtained from the primary trigger moment.

[0072] S402. For each rotor filter error value at a collection moment in the secondary phase-locked difference sequence, determine whether the rotor filter error value at the collection moment is greater than a preset threshold corresponding to the collection moment; if the rotor filter error value is greater than the preset threshold, write the rotor filter error value into a second exception queue.

[0073] S403: If the ratio of the total number of rotor filter error values in the second abnormal queue to the total number of rotor filter error values in the secondary phase-locked difference sequence is higher than the warning ratio, it is determined that the motor has a resolver fault.

[0074] Here, the warning ratio can be set to 90%, that is, if the rotor filter error value of 180ms within 200ms exceeds the corresponding preset threshold, it is determined that the motor has a resolver fault.

[0075] As an example, after determining that a resolver fault exists in the motor, the present application also sets different fault recovery mechanisms, including an automatic reset mechanism and a manual reset mechanism.

[0076] The automatic reset mechanism needs to meet multiple trigger conditions at the same time and the rotor filter error value Δθ needs to be filtered within 10 consecutive seconds. filter <0.01° (below 70% of the threshold), vehicle speed v≤5km / h (near stationary), and motor temperature Tm<80°C (to avoid false recovery at high temperatures). The technical basis for this is: the 10-second window ensures a non-transient decrease in error, effectively eliminating occasional noise interference; when the vehicle speed is ≤5km / h, the motor load is low and the resolver signal is most stable; and the temperature protection mechanism prevents secondary faults caused by signal drift due to high temperature.

[0077] The manual reset mechanism offers two methods: diagnostic tool command reset and power cycle reset. The diagnostic tool resets by sending reset command 0x55 through a standard diagnostic interface (such as OBD-II). During a power reset, the main control chip enters low-power mode after the key is turned off, and the fault flag is stored in non-volatile memory (EEPROM). Upon power cycle, the fault flag is automatically cleared if the motor temperature Tm is less than 80°C and the vehicle speed v = 0. To ensure the safety of the manual reset, strict safety checks are implemented, including a vehicle speed of 0°C to prevent accidental operation while driving, prohibiting manual reset when the motor temperature is above 80°C and requiring the motor to cool to a safe range, and requiring the diagnostic tool command to be signature-verified by the security chip (TMS570). To operate, connect the diagnostic tool to the fault management interface, send reset command 0x55, and wait for the system to respond with 0x55_OK. If the reset fails (e.g., due to overheating), the diagnostic tool will display an error code (such as 0xE1: Temperature Exceeded Limit). In terms of exception handling and safety assurance, an anti-sticking mechanism has been designed. If the automatic reset fails three times in a row after a fault is triggered, a permanent latch will be triggered (return to the factory for repair). After a successful reset, the fault history counter will be reset to zero to avoid false latching caused by cumulative counting. The safety monitoring layer is deeply involved. The automatic / manual reset instructions require synchronous confirmation of the main control chip (TC297) and the safety chip (TMS570). If Δθ>0.03° is detected during the reset process, the reset is immediately terminated and the power is forced to be reduced. At the same time, the system has a complete logging function, storing key data (Δθ, speed, temperature, etc.) 5 seconds before the fault occurs to form a fault snapshot, and recording the reset time, method (automatic / manual), and operator ID (diagnostic instrument certification) to meet ISO26262 audit requirements.

[0078] This fault recovery mechanism, through the aforementioned design, achieves intelligent recovery. Automatically resetting when conditions stabilize allows for seamless system recovery, reducing manual intervention. It is also safe and controllable, requiring multiple authentication steps for manual resets to prevent risks associated with misoperation. The system's self-healing, combined with an anti-stiction design and an abnormality-fusing mechanism, ensures long-term reliability after the fault is resolved. In practical applications, this mechanism enables the system to automatically recover in 95% of false triggering scenarios, while completely eliminating the miscorrection of actual faults. This meets ISO 26262 ASIL-C functional safety requirements and significantly improves the maintainability and safety of motor control systems.

[0079] As an example, this application also sets different processing strategies for different operating conditions.

[0080] Specifically, for the first working condition of full throttle over a speed bump, this application has formulated a special processing strategy corresponding to the first working condition, namely the torque limiting mode. The conditions for triggering the torque limiting mode include the following three: 1. Real-time calculation of the motor speed change rate, that is, the real-time acceleration α=dω / dt, when α>6000rpm / s² (the calibrable range is 6000~7000rpm / s²); 2. When the accelerator pedal signal is >95%, this prevents the sudden acceleration under partial pedaling from being misjudged; 3. The vehicle's Z-axis acceleration peak is detected by a three-axis vibration sensor. When the acceleration peak is >0.5g (gravity acceleration), it is used to match the speed bump impact characteristics. After all the above conditions are met, this application enables the gradient torque limiting algorithm as the control strategy. The main formula of the gradient torque limiting algorithm is:

[0081] Among them, T demand is the driver's requested torque, α is the real-time acceleration, and 0.8 is the attenuation coefficient that can be adjusted according to the motor characteristics.

[0082] At the same time, this application also sets a lower limit protection to ensure the maintenance of minimum power output and avoid stalling, specifically: T limit ≥0.3×T max T limit ≥0.3×T max , and limit the torque command slope to ≤500Nm / s to prevent torque mutations from exacerbating speed fluctuations. In terms of implementation steps, α and throttle opening are updated every 1ms. When α>6000, throttle opening>95%, and Z-axis impact>0.5g are achieved at the same time, the torque limit mode is activated and T is calculated according to the formula limit A rate of change limit of 500Nm / s is imposed. During the period when the torque limit is in effect, the timer of the fault trigger logic is suspended to avoid the accumulation of errors exceeding the limit. To ensure safety, the system sets up a dual mechanism. If the torque limit lasts for more than 5 seconds, it is forced to exit and restore the original torque to prevent function abuse. The torque limit instruction must be signed by the main control chip (TC297) and the security chip (TMS570) before it can be executed.

[0083] For the second working condition of braking on gravel roads, this application has formulated a special processing strategy corresponding to the second working condition, namely, the use of a back-electromotive force observer, whose triggering conditions comprehensively consider multiple factors, including wheel speed difference, braking pressure and vibration spectrum. Specifically: 1. Real-time monitoring is carried out using four-wheel independent wheel speed sensors. When the speed difference between any two wheels is detected to be >15km / h, it indicates that there is a significant difference in road adhesion. 2. Through the brake master cylinder pressure sensor, when the pressure is >50Bar, it can be determined as an emergency braking condition. 3. FFT analysis is performed on the vibration signal. If the energy proportion of the 5-15Hz frequency band is >40%, it meets the high-frequency vibration characteristics of gravel roads.

[0084] If all three conditions are met, the special handling strategy for gravel road braking is triggered, and the detection method of steps S101-S103 is disabled. Specifically, the detection method of steps S101-S103 is first disabled to avoid the misjudgment of speed signal distortion caused by tire slip. Then, the speed estimation method based on the back electromotive force observer is switched to. The specific formula of the speed estimation method is:

[0085] Specifically, K e is the back electromotive force constant, V phase is the phase voltage, I phase is the phase current, R is the motor resistance, and L is the motor inductance. The wheel speed difference, brake pressure and vibration spectrum data are collected synchronously every 10ms. When the wheel speed difference>15km / h, the brake pressure>50Bar and the energy proportion of the 5-15Hz frequency band>40% are established at the same time, the special processing strategy corresponding to the gravel road braking is triggered. In order to ensure the safety of the system operation, an independent monitoring window is set. If the error Δθ estimated by the backup algorithm is>0.03° and lasts for 1 second, the motor power is forced to be reduced to 30%. In addition, the present application also constructs multiple safety mechanisms: when the wheel speed difference is <5km / h and the brake pressure is <10Bar for 3 seconds, the system automatically restores the main detection function, that is, it is detected by the detection method of the above steps S101-S103; at the same time, the output of the back electromotive force observer and the speed feedback of the motor controller are redundantly checked. If the deviation between the two is>5%, the system will be triggered to run in a downgraded manner.

[0086] As an example, the present application has formulated a rigorous mechanism for triggering conflicts and data interaction requirements under special working conditions. When the first working condition and the second working condition are triggered at the same time (for example, a complex scenario such as full throttle braking on a gravel road), the system takes the gravel road mode as the priority execution item and directly disables the detection method of steps S101-S103 to avoid control instruction confusion due to interference from diagnostic logic. This priority logic is implemented through an embedded state machine to ensure that the system can still maintain behavioral determinism when multiple working conditions are superimposed and output stable and reliable control instructions. At the same time, during the activation of the gravel road mode, the working condition identification unit transmits working condition characteristic information to the dynamic threshold calibration module in real time, causing the preset threshold range to be relaxed to 0.018° to adapt to special working conditions such as tire slippage and speed signal fluctuations on gravel roads, ensuring that the system can effectively suppress interference and accurately capture real fault signals; and the threshold adjustment needs to be confirmed by the safety chip for the second time, while ensuring control flexibility, strengthening the system safety protection level.

[0087] The motor resolver fault detection solution of this application has the following specific beneficial effects: 1. Significantly reduce the false positive rate. Through dynamic filtering algorithms and dual verification mechanisms, the fault false trigger rate under extreme operating conditions such as full throttle over speed bumps and braking on gravel roads has been optimized and the algorithm has been strengthened compared to traditional methods, achieving zero false positives in some usage scenarios.

[0088] 2. Improved adaptability to working conditions: Dynamic threshold calibration (GPR model + real-time compensation) enables the system to improve and optimize the detection accuracy of phase-locked error compared to existing threshold methods in a temperature range of -30°C to 80°C and in severe vibration environments.

[0089] 3. Enhanced system real-time performance: dynamic filtering response delay <5ms, fault confirmation time <250ms, meeting ISO26262 ASIL-C real-time requirements, and significantly improving over traditional solutions.

[0090] 4. To ensure functional safety, the dual-core verification mechanism and fuse degradation strategy eliminate the risk of single point failure. The system security monitoring interception rate is high, meeting the highest functional safety level requirements of new energy vehicles.

[0091] 5. This application solves industry problems such as false triggering, missed detection, and response lag in resolver fault diagnosis through dynamic filtering, preset thresholds, and adaptive strategies for different working conditions. It achieves an order of magnitude improvement in core indicators such as misjudgment rate, real-time performance, and adaptability to working conditions, providing a breakthrough solution for high-reliability application scenarios such as new energy vehicles and industrial motors.

[0092] Based on the same inventive concept, an embodiment of the present application also provides a motor resolver fault detection device corresponding to the motor resolver fault detection method. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned motor resolver fault detection method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0093] See also Figure 5 , Figure 5 A schematic diagram of a motor resolver fault detection device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown in , the motor resolver fault detection device 500 includes: An acquisition module 501 is configured to acquire a phase-locked difference sequence of a motor; the phase-locked difference sequence includes rotor filter error values of the motor at a plurality of consecutive acquisition moments; each rotor filter error value is obtained based on a rotor error value and a rotational speed of the motor at a corresponding acquisition moment, and each rotor error value indicates a difference between an actual rotor angle value of the motor and an estimated rotor angle value of the motor at a corresponding acquisition moment.

[0094] The first identification module 502 is configured to identify a plurality of rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference abnormality rule is triggered.

[0095] The second identification module 503 is configured to identify whether the motor has a resolver fault based on the rotor filter error value corresponding to each sampling moment within a preset time period if the continuous difference abnormality rule is triggered.

[0096] See also Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown in FIG, the electronic device 600 includes a processor 610 , a memory 620 and a bus 630 .

[0097] The memory 620 stores machine-readable instructions executable by the processor 610. When the electronic device 600 is running, the processor 610 communicates with the memory 620 through the bus 630. When the machine-readable instructions are executed by the processor 610, the steps of the motor resolver fault detection method in the above-mentioned method embodiment can be executed. The specific implementation method can be found in the method embodiment and will not be repeated here.

[0098] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the motor resolver fault detection method in the above-mentioned method embodiment can be executed. The specific implementation method can be found in the method embodiment and will not be repeated here.

[0099] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0100] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. There may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interface, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms.

[0101] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0102] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0103] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, 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 and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0104] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-mentioned embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for detecting a motor resolver fault, characterized in that: The method comprises: Acquire a phase-locked difference value sequence of the motor; the phase-locked difference value sequence includes rotor filter error values of the motor at a plurality of consecutive acquisition moments; wherein each rotor filter error value is obtained based on a rotor error value of the motor and a rotational speed of the motor at a corresponding acquisition moment, and each rotor error value indicates a difference between an actual rotor angle value of the motor and an estimated rotor angle value of the motor at a corresponding acquisition moment; Identifying multiple rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference anomaly rule is triggered; If the continuous difference abnormality rule is triggered, whether the motor has a resolver fault is identified based on the rotor filter error value corresponding to each sampling moment within a preset time length.

2. The method according to claim 1, characterized in that Multiple rotor filter error values in the phase-locked difference sequence are identified by: For the rotor filter error value at each acquisition moment in the phase-locked difference sequence, determine whether the rotor filter error value at the acquisition moment is greater than a preset threshold corresponding to the acquisition moment; if the rotor filter error value is greater than the corresponding preset threshold, write the rotor filter error value into the first exception queue.

3. The method according to claim 2, characterized in that Determine whether to trigger the continuous difference anomaly rule in the following ways: Extracting the collection time corresponding to each rotor filter error value in the first abnormal queue; The extracted acquisition moments are identified for continuity, so that when it is identified that there are a predetermined number of rotor filter error values with consecutive acquisition moments in the first abnormal queue, the continuous difference abnormality rule is determined to be triggered, and the acquisition moment closest to the acquisition moment of all the predetermined number of rotor filter error values with consecutive acquisition moments in the first abnormal queue is determined as the primary triggering moment.

4. The method according to claim 3, characterized in that Identify whether the motor has a resolver fault by the following methods: Acquire a secondary phase-locked difference value sequence of the motor; the secondary phase-locked difference value sequence includes rotor filter error values of the motor at a plurality of consecutive acquisition moments within a preset time length, wherein the preset time length indicates a time length from the primary trigger moment to a preset end moment; For each rotor filter error value at a collection moment in the secondary phase-locked difference sequence, determining whether the rotor filter error value at the collection moment is greater than a preset threshold corresponding to the collection moment, and if the rotor filter error value is greater than the preset threshold, writing the rotor filter error value into a second abnormality queue; If the ratio between the total number of rotor filter error values in the second abnormal queue and the total number of rotor filter error values in the secondary phase-locked difference sequence is higher than the warning ratio, it is determined that the motor has a resolver fault.

5. The method according to claim 2, characterized in that Obtain the preset threshold corresponding to each collection moment in the following way: Obtaining a motor parameter data set corresponding to each preset acquisition time length of the motor, and obtaining a temperature change value and a vibration energy change value of the motor within each preset acquisition time length; wherein the motor parameter data set includes the motor operating parameters of the motor at each sampling moment within the corresponding preset acquisition time length; For each preset acquisition time, input the motor parameter data set of the preset acquisition time into the prediction model to obtain a basic threshold value corresponding to the preset acquisition time; For each preset collection time, the basic threshold corresponding to the preset collection time is corrected according to the temperature change value and vibration energy change value of the motor within the preset collection time to obtain the preset threshold corresponding to each sampling moment in the preset collection time.

6. The method according to claim 1, characterized in that The method further comprises: When the vehicle is in a first operating condition, a limiting torque value is obtained based on the requested torque value and the real-time acceleration change rate of the motor to control the motor to operate according to the limiting torque value. When it is detected that the speed change rate of the motor, the throttle opening of the vehicle and the Z-axis acceleration peak of the vehicle all exceed corresponding warning thresholds, it is determined that the vehicle is in the first operating condition.

7. The method according to claim 1, characterized in that The method further comprises: When the vehicle is in the second operating condition, a speed estimation value is obtained based on the phase voltage and phase current of the motor to control the motor to operate according to the speed estimation value. When it is detected that the vibration spectrum of the vehicle, the wheel speed difference of the vehicle and the brake pressure value of the vehicle all exceed corresponding warning thresholds, it is determined that the vehicle is in the second operating condition.

8. A motor resolver fault detection device, characterized in that: The device comprises: an acquisition module, configured to acquire a phase-locked difference value sequence of a motor; the phase-locked difference value sequence comprising rotor filter error values of the motor at a plurality of consecutive acquisition moments; wherein each rotor filter error value is obtained based on a rotor error value of the motor and a rotational speed of the motor at a corresponding acquisition moment, and each rotor error value indicates a difference between an actual rotor angle value of the motor and an estimated rotor angle value of the motor at a corresponding acquisition moment; A first identification module is used to identify multiple rotor filter error values in the phase-locked difference sequence to determine whether a continuous difference abnormality rule is triggered; The second identification module is used to identify whether the motor has a resolver fault based on the rotor filter error value corresponding to each sampling moment within a preset time period if the continuous difference abnormality rule is triggered.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of any one of the methods described in claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are executed.

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