Distributed driving safety redundancy system of axial flux motor

Abstract

The invention provides an axial flux motor distributed driving safety redundancy system which comprises a safety monitoring module, a fault diagnosis module, a fault early warning module, a main controller module, a redundancy controller module and a motor module. The signal end of the fault diagnosis module is connected with the signal end of the fault early warning module and the signal end of the safety monitoring module. According to the method, the data of multiple sensors are fused, the fault condition of the motor is predicted by comprehensively analyzing the data, the prediction accuracy is improved, the sensor data are trained and learned by adopting the fault prediction algorithm to identify the characteristics and modes of the motor fault, and the fault prediction accuracy is improved along with continuous accumulation of the data and continuous optimization of the algorithm. Compared with the prior art, the accuracy of the fault prediction algorithm can be continuously improved, and the method enables a driver or a maintainer to have enough time to take measures to solve the problem by finding potential fault risks in advance and sending out an early warning signal, thereby avoiding the occurrence or expansion of the fault.

Description

Technical Field

[0001] The invention relates to a safety redundant system, in particular to an axial flux motor distributed drive safety redundant system, belonging to the technical field of axial flux motor control. Background Art

[0002] Compared with traditional radial flux motors, the advantages of axial flux motors are that they have a more compact structure and lighter weight, which helps save vehicle space and reduce vehicle weight, thereby improving vehicle energy efficiency and range. The torque of the axial flux motor is proportional to the cube of the rotor radius, so it can provide higher torque and power output in the same volume, which is crucial to the acceleration performance and power performance of electric vehicles.

[0003] The distributed drive system allows independent control of the motor of each wheel, thereby achieving more flexible driving strategies and more precise handling performance. Under complex road conditions, the distributed drive system can improve the vehicle's traction and stability by adjusting the driving force distribution of different wheels. During braking, the distributed drive system can recover braking energy and convert it into electrical energy for storage, further improving energy efficiency. In a distributed drive system, each wheel is driven by an independent motor. When one of the motors fails, the other motors can take over to ensure the normal driving of the vehicle. This multi-motor backup mechanism is an important part of the safety redundancy system.

[0004] At present, the axial flux motor distributed drive safety redundancy system improves the reliability and safety of the system through distributed drive design and safety redundancy strategy. This system combines the advantages of the axial flux motor with the characteristics of distributed drive technology, aiming to improve the overall performance and ensure driving safety. However, in the existing technology, the axial flux motor distributed drive safety redundancy system still has the following technical problems: Due to its unique structure and working principle, the control algorithm of the axial flux motor is relatively complex, which requires accurate mathematical models and efficient algorithms to ensure the stable operation and performance optimization of the motor. However, due to the diversity and uncertainty of motor failures, the accuracy of the early warning algorithm is often difficult to guarantee, and thus the occurrence of failures cannot be effectively avoided. Therefore, a distributed drive safety redundant system for axial flux motors is proposed. Summary of the invention

[0005] In view of this, the present invention provides an axial flux motor distributed drive safety redundancy system to solve or alleviate the technical problems existing in the prior art and at least provide a beneficial option.

[0006] The technical solution of the embodiment of the present invention is implemented as follows: an axial flux motor distributed drive safety redundancy system, comprising a safety monitoring module, a fault diagnosis module, a fault warning module, a main controller module, a redundant controller module and a motor module, wherein the signal end of the fault diagnosis module is respectively connected to the signal end of the fault warning module and the signal end of the safety monitoring module, the signal end of the motor module is respectively connected to the signal end of the safety monitoring module, the signal end of the main controller module and the signal end of the redundant controller module, and the signal end of the fault diagnosis module is respectively connected to the signal end of the main controller module and the signal end of the redundant controller module; The safety monitoring module includes a temperature sensor, a vibration sensor and a current sensor, and the safety monitoring module is used to monitor the temperature data of various parts of the motor in real time, capture the vibration data generated during the operation of the motor, and monitor the motor current waveform and change rate data; The motor module includes a main motor and a redundant motor; The main controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the main motor to control the driving and braking of the vehicle; The redundant controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the redundant motor to control the driving and braking of the vehicle; The fault diagnosis module is used to predict potential faults using a fault prediction algorithm according to the operating state and parameter changes of the motor.

[0007] Further preferably, the fault prediction algorithm comprises the following steps: Step 1: Obtain temperature data, vibration data, current waveform and change rate data during the motor operation; Step 2: Clean the data and extract the features related to motor failure in the data, including temperature change trend, vibration spectrum characteristics and current harmonic content; Step 3: Based on the physical characteristics and fault modes of the motor, select features that are relevant to fault prediction and construct composite features, including the joint features of temperature and vibration, and the correlation analysis of current and magnetic flux density; Step 4: Select the gradient boosting tree as the base model, use the preprocessed data to train the base model, adjust the model parameters through cross-validation method, and optimize the prediction performance; Step 5: Use the weighted voting method to integrate the prediction results of each base model and adjust the weight according to the performance of the model on a specific fault type; Step 6: Integrate the prediction model into the control logic of the axial flux motor distributed drive safety redundant system. When the warning signal is triggered, the system automatically switches to the redundant motor and redundant controller module. Step 7: Adjust and optimize algorithm parameters and model structure based on actual feedback data, and introduce new sensor data and features to improve prediction accuracy; The fault warning module is used to receive the warning signal of the fault diagnosis module; In step five, when the prediction result of the model reaches the preset warning threshold, a warning signal is triggered and sent to the fault warning module. The warning signal includes the fault type, severity and expected occurrence time.

[0008] Further preferably, both the main motor and the redundant motor are axial flux motors, and when the main motor fails, the redundant motor starts to work.

[0009] Further preferably, the signal end of the motor module is connected to a thermal management module, and the thermal management module includes a temperature sensor, a fan and a heat sink; The thermal management module is used to monitor the operating temperatures of the main motor and the redundant motor, and the control logic in the thermal management module adjusts the operating states of the heat sink and the fan according to the temperature data.

[0010] Further preferably, the electrical end of the redundant motor is connected to a redundant power supply module, and the redundant power supply module is used to provide power support for the redundant motor. When the main motor fails, the redundant power supply module supplies power to the redundant motor.

[0011] Further preferably, the signal end of the fault warning module is connected to a user interaction module, and the user interaction module is used to provide vehicle status information, fault warning and driving suggestions.

[0012] Further preferably, the signal end of the user interaction module is connected to a data recording module, and the data recording module is used to record vehicle operation data and fault information to provide data support for subsequent fault analysis and performance optimization.

[0013] Further preferably, the signal end of the fault warning module and the signal end of the fault diagnosis module are both connected to the signal end of the data recording module.

[0014] Further preferably, the signal end of the user interaction module is connected to a remote support module, and the remote support module is used to connect to a remote server via a wireless network to achieve remote fault diagnosis, software upgrade and technical support.

[0015] Further preferably, the control end of the main controller module is connected to the signal end of the main motor, and the control end of the redundant controller module is connected to the signal end of the redundant motor.

[0016] Since the embodiment of the present invention adopts the above technical scheme, it has the following advantages: the present invention improves the accuracy of the prediction by fusing data from multiple sensors and comprehensively analyzing the data to predict the fault condition of the motor, and adopts a fault prediction algorithm to train and learn the sensor data to identify the characteristics and patterns of motor faults. With the continuous accumulation of data and continuous optimization of the algorithm, the accuracy of the fault prediction algorithm will continue to improve, thereby enabling the fault prediction algorithm to more accurately predict the fault condition of the motor and reduce false alarms and missed alarms. The present invention discovers potential fault risks in advance and sends out early warning signals, so that the driver or maintenance personnel have enough time to take measures to solve the problem, thereby avoiding the occurrence or expansion of faults.

[0017] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a structural diagram of the distributed drive safety redundancy system of the axial flux motor of the present invention.

[0021] Figure 2 It is a flow chart of the steps of the fault prediction algorithm of the present invention. DETAILED DESCRIPTION

[0022] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0023] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0024] like Figure 1-2As shown, an embodiment of the present invention provides an axial flux motor distributed drive safety redundant system, including a safety monitoring module, a fault diagnosis module, a fault warning module, a main controller module, a redundant controller module and a motor module, wherein the signal end of the fault diagnosis module is respectively connected to the signal end of the fault warning module and the signal end of the safety monitoring module, the signal end of the motor module is respectively connected to the signal end of the safety monitoring module, the signal end of the main controller module and the signal end of the redundant controller module, and the signal end of the fault diagnosis module is respectively connected to the signal end of the main controller module and the signal end of the redundant controller module; The safety monitoring module includes a temperature sensor, a vibration sensor and a current sensor. The safety monitoring module is used to monitor the temperature data of various parts of the motor in real time, capture the vibration data generated during the operation of the motor, and monitor the motor current waveform and change rate data; In the safety monitoring module, real-time monitoring of the temperature data of various parts of the motor, capturing the vibration data generated during the operation of the motor, and monitoring the motor current waveform and change rate data are important means to ensure the stable operation of the motor and timely detect potential faults. The following is a detailed description of these monitoring processes: 1. Real-time monitoring of temperature data of various parts of the motor Temperature sensor placement: Place temperature sensors at key locations of the motor, including windings, bearings, and housing. These sensors can be thermistors, thermocouples, or infrared thermometers. Data collection and transmission: The temperature sensor transmits the real-time collected temperature data to the safety monitoring module via cable or wirelessly; Data processing and display: After receiving the temperature data, the safety monitoring module processes and analyzes it, and displays the temperature values ​​of each part in real time on the monitoring interface; Through the above, the overheating of the motor can be detected in time to prevent safety accidents such as motor damage or fire caused by excessive temperature.

[0025] 2. Capture vibration data generated during motor operation Vibration sensor placement: Vibration sensors are placed at the bearings, base or other key parts of the motor; Data collection and transmission: The vibration sensor collects vibration data in real time, including acceleration, velocity, and displacement, and then transmits the data to the safety monitoring module; Data analysis and early warning: The safety monitoring module performs spectrum analysis and time domain analysis on vibration data to identify the vibration characteristics of the motor. When the vibration data is abnormal, an early warning signal is triggered; 3. Monitor motor current waveform and change rate data Current sensor arrangement: arrange the current sensor in the power line or control circuit of the motor; Data acquisition and transmission: The current sensor transmits the real-time collected current waveform and change rate data to the safety monitoring module; Data analysis and fault judgment: The safety monitoring module performs waveform analysis and change rate analysis on the current data to identify the current characteristics of the motor. When the current data is abnormal, such as waveform distortion or excessive change rate, an early warning signal is triggered; In summary, the safety monitoring module realizes comprehensive monitoring and early warning of the motor's operating status by arranging temperature sensors, vibration sensors and current sensors, and collecting, transmitting, processing and analyzing these data in real time. This helps to detect potential faults in time, prevent safety accidents and ensure the stable operation of the motor.

[0026] The motor module includes a main motor and a redundant motor; The main controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the main motor, control the driving and braking of the vehicle, ensure that the vehicle drives according to the driver's intention, and improve driving comfort and safety; The main controller module receives the control instructions from the fault diagnosis module and converts them into control signals for the main motor to control the driving and braking system of the vehicle. The specific process usually involves the following key steps: Signal reception and analysis: The main controller module first receives control instructions from the fault diagnosis module. These instructions contain information about the vehicle status, motor status, fault type and severity. The communication interface in the main controller module is responsible for receiving these instructions and parsing and converting them through the internal signal processing circuit; Control logic processing: The parsed instructions are passed to the core processing unit of the main controller module, which processes and analyzes the instructions according to the preset control algorithm and logic. This includes determining whether the vehicle should be in a driving state or a braking state, and the corresponding motor control parameters, including voltage, current, and frequency; Motor control signal generation: Based on the results of control logic processing, the main controller module generates corresponding motor control signals, including PWM signals, direction signals, and enable signals. The PWM signal is used to control the speed and torque of the motor, the direction signal is used to determine the rotation direction of the motor, and the enable signal is used to start or stop the motor. Signal amplification and transmission: The generated motor control signal needs to be amplified to ensure that it can drive the motor to work normally. The drive circuit in the main controller module is responsible for amplifying the control signal to an appropriate level and transmitting it to the main motor through a cable or bus; Motor response and execution: After receiving the control signal, the main motor performs corresponding driving or braking operations according to its internal electromagnetic principle and the instructions of the control signal, which includes adjusting the motor's speed, torque or direction to achieve functions such as acceleration, deceleration or parking of the vehicle; Feedback and adjustment: The main controller module also receives feedback signals from the main motor through sensors, such as current, voltage, and temperature. These feedback signals are used to monitor the operating status and performance of the motor and adjust and optimize the control signal according to the actual situation. This feedback mechanism can ensure that the motor always operates in the best condition and improve the driving comfort and safety of the vehicle. In summary, the main controller module receives control instructions from the fault diagnosis module and achieves precise control of vehicle driving and braking through steps such as analysis, processing, generating control signals, amplifying transmission, and motor response and execution. This process ensures the stable operation and safety of the vehicle under various working conditions.

[0027] The redundant controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the redundant motor, control the driving and braking of the vehicle, ensure the normal operation of the vehicle control system, enhance the fault tolerance of the system, and ensure the safe driving of the vehicle under extreme conditions; The fault diagnosis module is used to predict potential faults using a fault prediction algorithm based on the motor's operating status and parameter changes. By discovering potential faults in advance, it can provide a time window for repairs and replacement of parts, thus reducing losses caused by faults. The fault prediction algorithm includes the following steps: Step 1: Obtain temperature data, vibration data, current waveform and change rate data during the motor operation; Step 2: Clean the data to remove noise and outliers to ensure data accuracy and reliability. Extract features related to motor failures in the data, including temperature change trends, vibration spectrum features, and current harmonic content. Scale all feature values ​​to the same range to facilitate model training. Step 3: Based on the physical characteristics and fault modes of the motor, select features that are relevant to fault prediction. The relevant features take into account the special structure and working principle of the axial flux motor, such as magnetic field distribution, magnetic flux density and other factors; Construct composite features, including the joint features of temperature and vibration, and the correlation analysis of current and magnetic flux density, to more comprehensively reflect the operating status of the motor; Step 4: Select the gradient boosting tree as the base model, use the preprocessed data to train the base model, adjust the model parameters through cross-validation, optimize the prediction performance, pay special attention to the failure mode unique to the axial flux motor, and add relevant cases to the training data to improve the pertinence of the model; Step 5: Use the weighted voting method to integrate the prediction results of each base model, adjust the weight according to the performance of the model on a specific fault type, and improve the overall prediction accuracy; Step 6: Integrate the prediction model into the control logic of the axial flux motor distributed drive safety redundancy system. When the warning signal is triggered, the system automatically switches to the redundant motor and redundant controller modules to ensure that the vehicle can continue to drive safely. At the same time, the warning information is transmitted to the driver and maintenance personnel so that timely measures can be taken to solve the problem. Step 7: Adjust and optimize algorithm parameters and model structure according to actual feedback data, introduce new sensor data and features to improve prediction accuracy, and deploy the optimized algorithm to the real-time data processing unit of the system to ensure that the algorithm can run stably in a high-speed, low-latency environment to meet the needs of real-time warning.

[0028] In one embodiment, the fault warning module is used to receive the warning signal from the fault diagnosis module. When the prediction result of the model reaches a preset warning threshold, the warning signal is triggered and sent to the fault warning module. The warning signal includes the fault type, severity and expected occurrence time. The fault warning module is responsible for receiving the warning signals from the fault diagnosis module and triggering corresponding warning measures according to these signals. The warning algorithm is the core of the fault warning module, which determines the accuracy and timeliness of the warning signal. The warning algorithm includes the following steps: 1. Data Collection and Preprocessing Data collection: Collect real-time data from various sensors and monitoring points in the system. These data may include temperature, vibration, current, voltage and other parameters; Data preprocessing: Clean and format the collected data to remove noise and outliers to ensure data accuracy and consistency. At the same time, it may be necessary to perform feature extraction on the data to extract features that are useful for fault diagnosis. 2. Interaction of Fault Diagnosis Modules Receiving diagnosis results: The fault warning module interacts with the fault diagnosis module and receives the diagnosis results of the fault diagnosis module on the system status, including preliminary judgments such as fault type and fault degree; Set warning thresholds: According to the system's operating history and the recommendations of the fault diagnosis module, set reasonable warning thresholds. The thresholds vary depending on the fault type, system status, and operating environment. 3. Generation and judgment of early warning signals Model prediction: Use machine learning models to predict preprocessed data and determine whether the system is about to fail. The model is a time series prediction model; Warning signal generation: When the model's prediction results reach or exceed the preset warning threshold, the warning signal is triggered. The warning signal should contain information about the fault type, severity, and expected occurrence time; Signal verification: Before triggering the warning signal, the signal is further verified to ensure its accuracy and reliability, which is achieved by comparing it with other monitoring data or expert experience; IV. Early Warning Signal Transmission and Response Signal sending: Send the verified warning signal to the relevant interface or system of the fault warning module so that corresponding countermeasures can be taken; System response: After receiving the warning signal, the system automatically adjusts or issues an alarm according to the preset response strategy to remind the operator to take timely measures. The response strategy includes switching redundant equipment, adjusting operating parameters, and starting the emergency shutdown procedure; 5. Algorithm optimization and update Performance evaluation: Regularly evaluate the performance of the early warning algorithm, including accuracy, reliability, and timeliness, by comparing it with actual failure occurrences; Parameter adjustment: Based on the performance evaluation results, adjust and optimize the parameters of the early warning algorithm to improve its prediction accuracy and robustness; Model update: As the system operation time increases and fault data accumulates, the model used by the early warning algorithm needs to be updated regularly to adapt to changes in system status and new fault modes.

[0029] In one embodiment, both the main motor and the redundant motor are axial flux motors. When the main motor fails, the redundant motor works. The redundant motor takes over the work, thereby ensuring normal driving of the vehicle.

[0030] In one embodiment, the signal end of the motor module is connected to a thermal management module, and the thermal management module includes a temperature sensor, a fan, and a heat sink; The thermal management module is used to monitor the operating temperature of the main motor and redundant motor. The control logic in the thermal management module adjusts the working state of the heat sink and fan according to the temperature data, thereby ensuring that the motor operates within the appropriate temperature range; In the thermal management module, the control logic adjusts the working status of the heat sink and fan according to the data from the temperature sensor to ensure that the main motor and redundant motor operate within the appropriate temperature range. This process usually involves the following key steps: Data collection and monitoring: First, temperature sensors monitor the temperature of the motor and other key components in real time and send this data to the control logic of the thermal management module. Temperature sensors are placed in key parts of the motor, including windings, bearings, and housings, to ensure that temperature changes can be accurately captured. Data processing and judgment: Once the temperature data is received, the control logic will immediately process and analyze the data, and determine whether the motor is in a dangerous state of overheating or overcooling by comparing the current temperature with the preset threshold value (such as the upper and lower limits of the safe operating temperature range); Adjust heat sink and fan: Based on the analysis of temperature data, the control logic will make corresponding adjustment decisions: If the temperature is too high: the control logic will increase the speed of the heat sink and fan to improve the heat dissipation efficiency. This can be done by increasing the speed of the fan to speed up the air flow, or by adjusting the layout and number of heat sinks to enhance the heat dissipation effect. In some cases, the control logic may also start additional cooling systems, such as a coolant circulation system, to further reduce the temperature. If the temperature is moderate or too low: To save energy and extend the life of the device, the control logic will reduce the speed of the heat sink and fan, or shut them down completely; Feedback and adjustment: The control logic continuously monitors changes in temperature data and fine-tunes the working status of the heat sink and fan according to actual conditions. This feedback mechanism ensures that the motor always operates within the optimal temperature range, thereby improving its performance and reliability. Fault warning and protection: If the temperature data continues to be abnormal, the control logic will trigger the fault warning system to remind the operator to pay attention and take necessary measures. In some cases, the motor can be automatically shut down to prevent damage or safety accidents caused by overheating; In summary, the thermal management module can accurately adjust the working status of the heat sink and fan according to the temperature data through its internal control logic, thereby ensuring that the motor operates within the appropriate temperature range. This process not only improves the performance and reliability of the motor, but also extends its service life and reduces the risk of failure due to overheating.

[0031] In one embodiment, the electrical end of the redundant motor is connected to a redundant power supply module, which is used to provide power support for the redundant motor. When the main motor fails, the redundant power supply module supplies power to the redundant motor, thereby ensuring that key components can still work normally during power failure, improving the reliability and stability of the system, reducing the risk of system shutdown due to power failure, ensuring that the vehicle can continue to travel a certain distance during power failure, and improving safety.

[0032] In one embodiment, the signal end of the fault warning module is connected to a user interaction module, and the user interaction module is used to provide vehicle status information, fault warning and driving advice. The fault warning module is composed of the following structure: Dashboard: displays basic information such as vehicle speed, mileage, and battery level; Touch screen or buttons: used to set vehicle parameters, select driving mode, etc.; Voice control system: supports voice commands to control vehicle functions.

[0033] In one embodiment, the signal end of the user interaction module is connected to a data recording module, which is used to record vehicle operation data and fault information to provide data support for subsequent fault analysis and performance optimization. The signal end of the fault warning module and the signal end of the fault diagnosis module are both connected to the signal end of the data recording module, and data information can be recorded through the data recording module, thereby ensuring the safety of vehicle driving data.

[0034] In one embodiment, the signal end of the user interaction module is connected to a remote support module, and the remote support module is used to connect to a remote server via a wireless network to achieve remote fault diagnosis, software upgrades and technical support.

[0035] In one embodiment, the control end of the main controller module is connected to the signal end of the main motor, and the control end of the redundant controller module is connected to the signal end of the redundant motor. The working state of the main motor and the working state of the redundant motor can be controlled respectively through the main controller module and the redundant controller module.

[0036] When the present invention is working: the temperature data of the main motor is monitored by the safety monitoring module, the vibration data generated during the operation of the motor is captured, the motor current waveform and change rate data are monitored, and then the data is sent to the fault diagnosis module. The fault diagnosis module uses a fault prediction algorithm to predict potential faults based on the operating status and parameter changes of the motor. When the prediction result of the model reaches a preset warning threshold, a warning signal is triggered and sent to the fault warning module. At this time, the fault type, severity and expected occurrence time are displayed on the user interaction module. At the same time, the system automatically switches to the redundant motor and redundant controller module, and controls the operation of the redundant motor through the redundant control module.

[0037] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An axial flux motor distributed drive safety redundant system, comprising a safety monitoring module, a fault diagnosis module, a fault warning module, a main controller module, a redundant controller module and a motor module, characterized in that: The signal end of the fault diagnosis module is respectively connected to the signal end of the fault warning module and the signal end of the safety monitoring module, the signal end of the motor module is respectively connected to the signal end of the safety monitoring module, the signal end of the main controller module and the signal end of the redundant controller module, and the signal end of the fault diagnosis module is respectively connected to the signal end of the main controller module and the signal end of the redundant controller module; The safety monitoring module includes a temperature sensor, a vibration sensor and a current sensor, and the safety monitoring module is used to monitor the temperature data of various parts of the motor in real time, capture the vibration data generated during the operation of the motor, and monitor the motor current waveform and change rate data; The motor module includes a main motor and a redundant motor; The main controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the main motor to control the driving and braking of the vehicle; The redundant controller module is used to receive the control instructions of the fault diagnosis module and convert them into control signals of the redundant motor to control the driving and braking of the vehicle; The fault diagnosis module is used to predict potential faults using a fault prediction algorithm according to the operating state and parameter changes of the motor.

2. The axial flux motor distributed drive safety redundancy system according to claim 1, characterized in that: The fault prediction algorithm comprises the following steps: Step 1: Obtain temperature data, vibration data, current waveform and change rate data during the motor operation; Step 2: Clean the data and extract the features related to motor failure in the data, including temperature change trend, vibration spectrum characteristics and current harmonic content; Step 3: Based on the physical characteristics and fault modes of the motor, select features that are relevant to fault prediction and construct composite features, including the joint features of temperature and vibration, and the correlation analysis of current and magnetic flux density; Step 4: Select the gradient boosting tree as the base model, use the preprocessed data to train the base model, adjust the model parameters through cross-validation method, and optimize the prediction performance; Step 5: Use the weighted voting method to integrate the prediction results of each base model and adjust the weight according to the performance of the model on a specific fault type; Step 6: Integrate the prediction model into the control logic of the axial flux motor distributed drive safety redundant system. When the warning signal is triggered, the system automatically switches to the redundant motor and redundant controller module. Step 7: Adjust and optimize algorithm parameters and model structure based on actual feedback data, and introduce new sensor data and features to improve prediction accuracy; The fault warning module is used to receive the warning signal of the fault diagnosis module; In step five, when the prediction result of the model reaches the preset warning threshold, a warning signal is triggered and sent to the fault warning module. The warning signal includes the fault type, severity and expected occurrence time.

3. The axial flux motor distributed drive safety redundancy system according to claim 2, characterized in that: The main motor and the redundant motor are both axial flux motors. When the main motor fails, the redundant motor starts to work.

4. The axial flux motor distributed drive safety redundancy system according to claim 3, characterized in that: The signal end of the motor module is connected to a thermal management module, and the thermal management module includes a temperature sensor, a fan and a heat sink; The thermal management module is used to monitor the operating temperatures of the main motor and the redundant motor, and the control logic in the thermal management module adjusts the operating states of the heat sink and the fan according to the temperature data.

5. The axial flux motor distributed drive safety redundancy system according to claim 4, characterized in that: The electrical end of the redundant motor is connected to a redundant power supply module, and the redundant power supply module is used to provide power support for the redundant motor. When the main motor fails, the redundant power supply module supplies power to the redundant motor.

6. The axial flux motor distributed drive safety redundancy system according to claim 5, characterized in that: The signal end of the fault warning module is connected to a user interaction module, and the user interaction module is used to provide vehicle status information, fault warning and driving suggestions.

7. The axial flux motor distributed drive safety redundancy system according to claim 6, characterized in that: The signal end of the user interaction module is connected to a data recording module, and the data recording module is used to record vehicle operation data and fault information to provide data support for subsequent fault analysis and performance optimization.

8. The axial flux motor distributed drive safety redundancy system according to claim 7, characterized in that: The signal end of the fault warning module and the signal end of the fault diagnosis module are both connected to the signal end of the data recording module.

9. The axial flux motor distributed drive safety redundancy system according to claim 8, characterized in that: The signal end of the user interaction module is connected to a remote support module, and the remote support module is used to connect to a remote server through a wireless network to achieve remote fault diagnosis, software upgrade and technical support.

10. The axial flux motor distributed drive safety redundancy system according to claim 9, characterized in that: The control end of the main controller module is connected to the signal end of the main motor, and the control end of the redundant controller module is connected to the signal end of the redundant motor.

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