Motor control system and control method thereof

Abstract

The invention relates to the technical field of electric motorcycles, and discloses a motor control system and method, and the system comprises a motor controller, a 5G communication module, a battery management system, a safety mechanism module, and an artificial intelligence module. The motor controller is used for receiving and processing control signals from the 5G communication module and the artificial intelligence module so as to control operation of the motor, and the 5G communication module is used for receiving control signals from external equipment and transmitting the signals to the motor controller. Meanwhile, running state data of the motor and a learning result obtained from the artificial intelligence module are transmitted to external equipment in real time, and the battery management system is used for monitoring the state of the battery. The motor control system is mainly composed of the motor controller, the 5G communication module, the battery management system, the safety mechanism module and the artificial intelligence module, the modules work cooperatively through the 5G communication module and the artificial intelligence module, and accurate control and efficient operation of the motor can be achieved.

Description

Technical Field

[0001] This invention belongs to the field of electric motorcycle technology, specifically, it relates to a control system and control method for an electric motor. Background Technology

[0002] With the development of technology, electric motorcycles have become an important choice for people's daily travel. However, traditional electric motorcycle motor control systems have limitations in data transmission speed, response time, and system coordination, which to some extent restricts the performance improvement and user experience of electric motorcycles. Secondly, motors may malfunction during operation, such as winding short circuits and bearing wear. Traditional motor control systems are insufficient in fault detection and diagnosis, often relying on manual inspection and maintenance, which not only affects maintenance efficiency but may also increase maintenance costs. Therefore, it is necessary to introduce 5G communication technology and artificial intelligence modules into the electric motorcycle motor control system to improve system performance and collaborative capabilities, providing riders with a better riding experience. Simultaneously, introducing a fault detection module, combined with the artificial intelligence module system, enables autonomous fault detection and diagnosis, improving system reliability and maintenance efficiency.

[0003] In view of this, the present invention is proposed. Summary of the Invention

[0004] To solve the above-mentioned technical problems, the basic concept of the technical solution adopted by the present invention is as follows:

[0005] A motor control system includes a motor controller, a 5G communication module, a battery management system, a safety mechanism module, and an artificial intelligence module. The motor controller receives and processes control signals from the 5G communication module and the artificial intelligence module to control the operation of the motor. The 5G communication module receives control signals from external devices and transmits these signals to the motor controller. Simultaneously, it transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time. The battery management system monitors the battery status and sends this information to the external devices via the 5G communication module. The safety mechanism module ensures the data transmission security of the 5G communication module.

[0006] In a preferred embodiment of the present invention, the external devices include, but are not limited to, intelligent transportation systems, autonomous driving systems, remote monitoring systems, charging stations, service centers, emergency rescue systems, and mobile communication devices.

[0007] In a preferred embodiment of the present invention, the intelligent transportation system can monitor road conditions, traffic flow and other information in real time, and transmit this information to the motor control system via a 5G network. The motor control system can adjust the operating state of the motor based on the received data to achieve more efficient traffic flow management. The autonomous driving system needs to obtain environmental information around the vehicle in real time. Through 5G communication with the motor control system, the autonomous driving system can quickly obtain the operating state of the vehicle and send control commands to the motor control system to realize the autonomous driving function.

[0008] In a preferred embodiment of the present invention, the remote monitoring system can acquire vehicle operating data in real time via a 5G network, including but not limited to speed, acceleration, and battery level; the charging station or charging pile can communicate with the motor control system via a 5G network to acquire the vehicle's charging needs and charging status.

[0009] In a preferred embodiment of the present invention, the service center or repair station can receive vehicle operating data through a 5G network to perform fault diagnosis and predictive maintenance. When a vehicle malfunctions, it can quickly locate the problem and provide a solution. In the event of an accident or emergency, the emergency rescue system can communicate with the motor control system through the 5G network to obtain information such as the vehicle's location and status, so as to quickly carry out rescue operations.

[0010] In a preferred embodiment of the present invention, the artificial intelligence module is able to learn on its own, understand or master the rider's riding habits, and optimize the motor control strategy based on the learning results to better meet the rider's riding needs.

[0011] In a preferred embodiment of the present invention, a fault detection module is also included. The fault detection module can monitor the operating status of the motor in real time. When a fault is detected, it will autonomously diagnose the fault type and send the fault information to external devices, including but not limited to service centers and repair stations, through the 5G communication module. The fault detection module will also send the fault data to the artificial intelligence module system so that the system can learn and optimize autonomously.

[0012] In a preferred embodiment of the present invention, the fault detection module can monitor the operating status of the motor in real time, including but not limited to current, voltage and temperature parameters.

[0013] In a preferred embodiment of the present invention, the artificial intelligence module further includes a data collection and processing submodule, a fault feature extraction submodule, a fault diagnosis and prediction submodule, and a self-optimization and learning submodule. The data collection and processing submodule is responsible for collecting raw motor operation data from the fault detection module and other related modules, and converting the data into a format suitable for subsequent analysis and learning after preprocessing. The fault feature extraction submodule uses deep learning and feature engineering techniques to extract fault features from the preprocessed data. Fault features include, but are not limited to, frequency components, waveform changes, and statistical indicators. Fault features reflect the health status of the motor and potential fault modes. The fault diagnosis and prediction submodule uses machine learning algorithms to classify and predict faults based on the extracted fault features. The self-optimization and learning submodule is responsible for adjusting and optimizing the parameters and structure of the model based on the feedback of the fault diagnosis results to improve the accuracy and efficiency of the diagnosis. As the system runs for a longer period of time, the model will continuously accumulate learning experience and autonomously optimize its performance.

[0014] A control method for a motor control system includes the following steps:

[0015] Step 1: The motor controller receives control signals from the 5G communication module and the artificial intelligence module. The motor controller processes these control signals and adjusts the motor's operating status, such as speed, direction, or power output, according to the signal content.

[0016] Step 2: The 5G communication module receives control signals from external devices and transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time.

[0017] Step 3: The battery management system monitors the battery status, including key parameters such as charge, voltage, and temperature. If an abnormal battery status is detected, the battery management system will send a warning signal to the motor controller and may trigger a safety mechanism.

[0018] Step 4: The security mechanism module ensures the security of data transmission of the 5G communication module and prevents unauthorized access or malicious attacks; if any security threat is detected, the security mechanism module will take immediate measures, such as disconnecting the communication connection or initiating an emergency response procedure.

[0019] Step 5: The artificial intelligence module collects and analyzes the motor's operating data and learns the rider's riding habits; based on the learning results, the artificial intelligence module optimizes the motor control strategy to better meet the rider's riding needs.

[0020] Step 6: The fault detection module monitors the motor's operating status in real time. If a fault is detected, the fault detection module will autonomously diagnose the fault type and send the fault information to the service center or repair station via the 5G communication module. At the same time, the fault data will also be sent to the artificial intelligence module for autonomous learning and optimization to improve the system's reliability and performance.

[0021] Step 7: As the system runs longer, the artificial intelligence module will continuously accumulate learning experience and autonomously optimize its performance.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] 1. The motor control system of the present invention mainly consists of a motor controller, a 5G communication module, a battery management system, a safety mechanism module and an artificial intelligence module. These modules work together through the 5G communication module and the artificial intelligence module to achieve precise control and efficient operation of the motor.

[0024] 2. Through the 5G communication module, the system of this invention can communicate with a variety of external devices, including but not limited to intelligent transportation systems, autonomous driving systems, remote monitoring systems, charging stations, service centers, emergency rescue systems, and mobile communication devices. The extensive connectivity enables the motor control system to receive and send data in real time, thereby realizing remote monitoring and control of the motor. This not only achieves intelligent communication connectivity but also enhances safety from the perspective of driving and riding.

[0025] 3. The artificial intelligence module of this invention can learn the rider's riding habits and optimize the motor control strategy based on the learning results to better meet the rider's riding needs. Furthermore, artificial intelligence can also be used for fault diagnosis and prediction, improving the accuracy and efficiency of fault diagnosis by analyzing and learning from historical data.

[0026] 4. The fault detection module of this invention can monitor the motor's operating status in real time, including parameters such as current, voltage, and temperature. When a fault is detected, it will autonomously diagnose the fault type and send the fault information to external devices via the 5G communication module. Simultaneously, the fault data will also be sent to the artificial intelligence module for autonomous learning and optimization to improve the system's reliability and performance.

[0027] The specific embodiments of the present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0028] In the attached diagram:

[0029] Figure 1 This is a block diagram of the control system of the present invention;

[0030] Figure 2This is a flowchart of the control method of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments will be clearly and completely described below with reference to the accompanying drawings. The following embodiments are used to illustrate the present invention.

[0032] A control system for an electric motor, such as Figure 1 As shown, the system includes a motor controller, a 5G communication module, a battery management system, a safety mechanism module, and an artificial intelligence module. The motor controller receives and processes control signals from the 5G communication module and the artificial intelligence module to control the operation of the motor. The 5G communication module receives control signals from external devices and transmits these signals to the motor controller. At the same time, it transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time. The battery management system monitors the battery status and sends this information to the external devices through the 5G communication module. The safety mechanism module ensures the data transmission security of the 5G communication module.

[0033] The external devices include, but are not limited to, intelligent transportation systems, autonomous driving systems, remote monitoring systems, charging stations, service centers, emergency rescue systems, and mobile communication devices.

[0034] The intelligent transportation system can monitor road conditions and traffic flow in real time and transmit this information to the motor control system via a 5G network. Based on the received data, the motor control system can adjust the motor's operating status to achieve more efficient traffic flow management. The autonomous driving system needs to obtain real-time environmental information about the vehicle's surroundings. Through 5G communication with the motor control system, the autonomous driving system can quickly obtain the vehicle's operating status and send control commands to the motor control system to achieve autonomous driving functionality.

[0035] The remote monitoring system can acquire vehicle operating data in real time via the 5G network, including but not limited to speed, acceleration, and battery level; the charging station or charging pile can communicate with the motor control system via the 5G network to obtain the vehicle's charging needs and charging status.

[0036] The service center or repair station can receive vehicle operation data through the 5G network to perform fault diagnosis and predictive maintenance. When a vehicle malfunctions, it can quickly locate the problem and provide a solution. In the event of an accident or emergency, the emergency rescue system can communicate with the motor control system through the 5G network to obtain information such as the vehicle's location and status, so as to carry out rescue operations quickly.

[0037] The artificial intelligence module can learn on its own, understand or master the rider's riding habits, and optimize the motor control strategy based on the learning results to better meet the rider's riding needs.

[0038] It also includes a fault detection module, which can monitor the motor's operating status in real time. When a fault is detected, it will autonomously diagnose the fault type and send the fault information to external devices, including but not limited to service centers and repair stations, via a 5G communication module. The fault detection module will also send fault data to an artificial intelligence module system so that the system can learn and optimize itself. The fault detection module can monitor the motor's operating status in real time, including but not limited to current, voltage, and temperature parameters.

[0039] The artificial intelligence module further includes a data collection and processing submodule, a fault feature extraction submodule, a fault diagnosis and prediction submodule, and a self-optimization and learning submodule. The data collection and processing submodule is responsible for collecting raw motor operation data from the fault detection module and other related modules, and converting the data into a format suitable for subsequent analysis and learning after preprocessing. The fault feature extraction submodule uses deep learning and feature engineering techniques to extract fault features from the preprocessed data. Fault features include, but are not limited to, frequency components, waveform changes, and statistical indicators. Fault features reflect the health status of the motor and potential fault modes. The fault diagnosis and prediction submodule uses machine learning algorithms to classify and predict faults based on the extracted fault features. The self-optimization and learning submodule is responsible for adjusting and optimizing the parameters and structure of the model based on the feedback from the fault diagnosis results, improving the accuracy and efficiency of the diagnosis. As the system runs for a longer period of time, the model will continuously accumulate learning experience and autonomously optimize its performance.

[0040] The motor control system of the present invention mainly consists of a motor controller, a 5G communication module, a battery management system, a safety mechanism module, and an artificial intelligence module. These modules work together through the 5G communication module and the artificial intelligence module to achieve precise control and efficient operation of the motor.

[0041] This invention utilizes a 5G communication module, enabling the system to communicate with various external devices, including but not limited to intelligent transportation systems, autonomous driving systems, remote monitoring systems, charging stations, service centers, emergency rescue systems, and mobile communication devices. This extensive connectivity allows the motor control system to receive and send data in real time, thereby enabling remote monitoring and control of the motor. This not only achieves intelligent communication connectivity but also enhances safety from a driving and riding perspective.

[0042] The remote monitoring system of this invention can acquire vehicle operating data, such as speed, acceleration, and battery level, in real time via a 5G network. Charging stations or charging piles can then communicate with the motor control system via the 5G network to obtain the vehicle's charging needs and charging status information, thereby enabling optimized management of the charging process.

[0043] This invention allows service centers or repair stations to receive vehicle operating data via a 5G network for fault diagnosis and predictive maintenance. When a vehicle malfunctions, the system can quickly locate the problem and provide a solution. The emergency rescue system can also obtain the vehicle's location and status information through 5G communication with the motor control system, enabling rapid rescue in emergency situations.

[0044] A control method for a motor control system, such as Figure 2 As shown, the work steps include the following:

[0045] Step 1: The motor controller receives control signals from the 5G communication module and the artificial intelligence module. The motor controller processes these control signals and adjusts the motor's operating status, such as speed, direction, or power output, according to the signal content.

[0046] Step 2: The 5G communication module receives control signals from external devices and transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time.

[0047] Step 3: The battery management system monitors the battery status, including key parameters such as charge, voltage, and temperature. If an abnormal battery status is detected, the battery management system will send a warning signal to the motor controller and may trigger a safety mechanism.

[0048] Step 4: The security mechanism module ensures the security of data transmission of the 5G communication module and prevents unauthorized access or malicious attacks; if any security threat is detected, the security mechanism module will take immediate measures, such as disconnecting the communication connection or initiating an emergency response procedure.

[0049] Step 5: The artificial intelligence module collects and analyzes the motor's operating data and learns the rider's riding habits; based on the learning results, the artificial intelligence module optimizes the motor control strategy to better meet the rider's riding needs.

[0050] Step 6: The fault detection module monitors the motor's operating status in real time. If a fault is detected, the fault detection module will autonomously diagnose the fault type and send the fault information to the service center or repair station via the 5G communication module. At the same time, the fault data will also be sent to the artificial intelligence module for autonomous learning and optimization to improve the system's reliability and performance.

[0051] Step 7: As the system runs longer, the artificial intelligence module will continuously accumulate learning experience and autonomously optimize its performance.

[0052] The artificial intelligence module of this invention can learn riders' riding habits and optimize motor control strategies based on the learning results to better meet the riders' riding needs. Furthermore, artificial intelligence can also be used for fault diagnosis and prediction, improving the accuracy and efficiency of fault diagnosis by analyzing and learning from historical data.

[0053] The fault detection module of this invention can monitor the operating status of the motor in real time, including parameters such as current, voltage, and temperature. When a fault is detected, it will autonomously diagnose the fault type and send the fault information to external devices via a 5G communication module. Simultaneously, the fault data will also be sent to an artificial intelligence module for autonomous learning and optimization to improve the system's reliability and performance.

[0054] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A control system for an electric motor, characterized in that, It includes a motor controller, a 5G communication module, a battery management system, a safety mechanism module, and an artificial intelligence module. The motor controller receives and processes control signals from the 5G communication module and the artificial intelligence module to control the operation of the motor. The 5G communication module receives control signals from external devices and transmits these signals to the motor controller. At the same time, it transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time. The battery management system monitors the battery status and sends this information to the external devices through the 5G communication module. The safety mechanism module ensures the data transmission security of the 5G communication module.

2. The control system for the motor according to claim 1, characterized in that, The external devices include, but are not limited to, intelligent transportation systems, autonomous driving systems, remote monitoring systems, charging stations, service centers, emergency rescue systems, and mobile communication devices.

3. The control system for the motor according to claim 2, characterized in that, The intelligent transportation system can monitor road conditions and traffic flow in real time and transmit this information to the motor control system via a 5G network. Based on the received data, the motor control system can adjust the motor's operating status to achieve more efficient traffic flow management. The autonomous driving system needs to obtain real-time environmental information about the vehicle's surroundings. Through 5G communication with the motor control system, the autonomous driving system can quickly obtain the vehicle's operating status and send control commands to the motor control system to achieve autonomous driving functionality.

4. The control system for the motor according to claim 2, characterized in that, The remote monitoring system can acquire vehicle operating data in real time via the 5G network, including but not limited to speed, acceleration, and battery level; the charging station or charging pile can communicate with the motor control system via the 5G network to obtain the vehicle's charging needs and charging status.

5. The control system for the motor according to claim 2, characterized in that, The service center or repair station can receive vehicle operation data through the 5G network to perform fault diagnosis and predictive maintenance. When a vehicle malfunctions, it can quickly locate the problem and provide a solution. In the event of an accident or emergency, the emergency rescue system can communicate with the motor control system through the 5G network to obtain information such as the vehicle's location and status, so as to carry out rescue operations quickly.

6. The control system for the motor according to claim 1, characterized in that, The artificial intelligence module can learn on its own, understand or master the rider's riding habits, and optimize the motor control strategy based on the learning results to better meet the rider's riding needs.

7. The control system for the motor according to claim 1, characterized in that, It also includes a fault detection module, which can monitor the motor's operating status in real time. When a fault is detected, it will autonomously diagnose the fault type and send the fault information to external devices, including but not limited to service centers and repair stations, via the 5G communication module. The fault detection module will also send the fault data to the artificial intelligence module system so that the system can learn and optimize autonomously.

8. The control system for the motor according to claim 7, characterized in that, The fault detection module can monitor the motor's operating status in real time, including but not limited to current, voltage, and temperature parameters.

9. The control system for the motor according to claim 7, characterized in that, The artificial intelligence module includes a data collection and processing submodule, a fault feature extraction submodule, a fault diagnosis and prediction submodule, and a self-optimization and learning submodule. The data collection and processing submodule is responsible for collecting raw motor operation data from the fault detection module and other related modules, and converting the data into a format suitable for subsequent analysis and learning after preprocessing. The fault feature extraction submodule utilizes deep learning and feature engineering techniques to extract fault features from preprocessed data. Fault features include, but are not limited to, frequency components, waveform changes, and statistical indicators. Fault characteristics reflect the health status and potential fault modes of the motor; the fault diagnosis and prediction submodule uses machine learning algorithms to classify and predict faults based on the extracted fault characteristics. The self-optimization and learning submodule is responsible for adjusting and optimizing the model's parameters and structure based on the feedback from fault diagnosis results, thereby improving the accuracy and efficiency of diagnosis. As the system runs for longer, the model will continuously accumulate learning experience and autonomously optimize its performance.

10. A control method for a motor control system, characterized in that, The work includes the following steps: Step 1: The motor controller receives control signals from the 5G communication module and the artificial intelligence module. The motor controller processes these control signals and adjusts the motor's operating status, such as speed, direction, or power output, according to the signal content. Step 2: The 5G communication module receives control signals from external devices and transmits the motor's operating status data and the learning results obtained from the artificial intelligence module to the external devices in real time. Step 3: The battery management system monitors the battery status, including key parameters such as charge, voltage, and temperature. If an abnormal battery status is detected, the battery management system will send a warning signal to the motor controller and may trigger a safety mechanism. Step 4: The security mechanism module ensures the security of data transmission of the 5G communication module and prevents unauthorized access or malicious attacks; if any security threat is detected, the security mechanism module will take immediate measures, such as disconnecting the communication connection or initiating an emergency response procedure. Step 5: The artificial intelligence module collects and analyzes the motor's operating data and learns the rider's riding habits; Based on the learning results, the artificial intelligence module optimizes the motor control strategy to better meet the rider's riding needs; Step 6: The fault detection module monitors the motor's operating status in real time. If a fault is detected, the fault detection module will autonomously diagnose the fault type and send the fault information to the service center or repair station via the 5G communication module. At the same time, the fault data will also be sent to the artificial intelligence module for autonomous learning and optimization to improve the system's reliability and performance. Step 7: As the system runs longer, the artificial intelligence module will continuously accumulate learning experience and autonomously optimize its performance.

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