Data transmission system and method applied to motor adaptive control

Abstract

The invention discloses a data transmission system and method applied to motor adaptive control, and relates to the technical field of data transmission, the method comprises the following steps: a communication bus connects a motor controller and a motor sensor to form a unified communication mechanism; preprocessing the data acquired by the motor sensor, and extracting feature data; using a random forest model to identify a driving mode; calculating a communication rate; generating a check code by using cyclic redundancy check, attaching the check code to the tail of the data packet and sending the check code to a motor controller; the motor controller receives the data packet and verifies the accuracy of the data; and the communication rate is dynamically adjusted, and the working state of the motor and the data transmission condition are monitored in the data transmission process. According to the identified driving mode and the motor state, the communication rate and the control strategy are automatically adjusted, and the data transmission and the motor performance are optimized; by monitoring the power and energy consumption of the motor in real time, the motor operation is optimized, and the energy consumption is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a data transmission system and method applied to motor adaptive control. Background Art

[0002] With the development of electric vehicles, the accuracy and reliability of motor control systems are becoming increasingly important. In order to improve the motor control performance, it is usually necessary to monitor the various operating parameters of the motor in real time and make fast and accurate control decisions based on them. Therefore, efficient motor data transmission has become a research hotspot. Currently, most motor control systems on the market use fixed communication protocols and rate settings. Although this approach is simple, it lacks flexibility and cannot achieve optimal data transmission efficiency when facing different working conditions, which may affect the response speed and stability of the overall system.

[0003] Currently, two strategies are commonly adopted to solve this problem: one is to use a high-bandwidth communication bus to ensure sufficient data throughput; the other is to increase the cache space to smooth out bursty data flows and reduce data loss caused by excessive instantaneous traffic.

[0004] Both of these common methods have obvious limitations. High-bandwidth communication solutions increase hardware costs and energy consumption. Relying solely on cache mechanisms is difficult to cope with the complex and changeable actual operating environment, especially in situations where frequent switching of drive modes is required. The traditional fixed configuration method is prone to data transmission delays or even failures, thereby reducing the overall efficiency of the motor control system. Summary of the invention

[0005] The object of the present invention is to provide a data transmission system and method for motor adaptive control to solve the problems raised in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solution: a data transmission method for motor adaptive control, the method comprising the steps of: S1, connecting the motor controller and the motor sensor through a communication bus to form a unified communication mechanism; S2. Preprocess the data collected by the motor sensor, extract feature data, and construct new features through the feature data; use the random forest model to identify the driving mode; S3, calculating the communication rate according to the driving pattern, feature data and new features identified by the random forest model; S4, using cyclic redundancy check to generate a check code, appending it to the end of the data packet and sending it to the motor controller; the motor controller receives the data packet and verifies the accuracy of the data; S5. Dynamically adjust the communication rate and monitor the working status of the motor and the data transmission status during the data transmission process.

[0007] According to the above scheme, in step S1: The motor controller is connected to at least one motor sensor through a communication bus to form a unified bus system; the motor controller sends a query request to the motor sensor; the motor controller receives the working status of the motor returned by the motor sensor; the working status includes the motor's speed, current, voltage and torque.

[0008] According to the above scheme, in step S2: Preprocessing the collected data, including missing value processing, outlier detection and feature scaling; extracting feature data from the preprocessed data, including motor speed, current, voltage and torque; and constructing new features through the feature data, including motor acceleration, power and energy consumption; Combine feature data and constructed new features into a dataset, and divide the dataset into a training set and a test set; A random forest model is constructed, and a driving mode is predicted and identified through the random forest model; the driving mode includes an urban driving mode and a highway driving mode.

[0009] According to the above scheme, the acceleration of the motor is expressed as the rate of change of the motor speed, and the formula is as follows: ; Where a represents the acceleration of the motor; ΔRPM represents the change in speed; Δt represents the change in time; The power of the motor is expressed as the output power of the motor, and the formula is as follows: P = J × RPM × 2π / 60; Among them, P represents the power of the motor; J represents the torque; RPM represents the speed; The energy consumption of the motor is expressed as the electric energy consumed by the motor during operation, and the formula is as follows: N = I × U; Among them, N represents the electric energy of the motor; I represents the current of the motor; U represents the voltage of the motor.

[0010] According to the above scheme, the number of decision trees constructed is n; for each decision tree, a subset is extracted from the training set with replacement to form a new sample set; k features are randomly selected from the m features; among the selected k features, Gini impurity is used as an evaluation index, and the feature that minimizes the Gini impurity and its corresponding split point are selected as the splitting condition of the node to construct a decision tree; the Gini impurity is an indicator for evaluating the purity of the data set in the classification problem; The Gini impurity formula is as follows: ; Among them, Gini(p) represents the Gini impurity; k represents the total number of feature categories; p i It is expressed as the proportion of category i in the node; Use the training set data to train each tree to generate a random forest model; Use the test set to evaluate the model. For each test sample, use the random forest model to make predictions and obtain the prediction results of multiple decision trees. Vote for the prediction results of all decision trees and select the category with the most votes as the final prediction result. The formula is as follows: ; Among them, Y represents the prediction result; n represents the total number of decision trees; y j is the prediction result of the jth decision tree; Ⅱ is the indicator function; Ⅱ(y j =y i ) is expressed as the prediction result y for each decision tree j j , check whether it is equal to the currently considered category y i , if yes, then 1; if no, then 0; In city driving, the vehicle starts and stops frequently, the motor speed changes greatly, the motor acceleration is high, and the motor energy consumption is high; During highway driving, the vehicle travels at a relatively stable speed, the motor speed changes little, the motor acceleration is low, and the motor energy consumption is relatively low.

[0011] According to the above scheme, in step S3: According to the identified driving mode, the communication rate is calculated as follows: X=b 0 +b 1 ×M+b 2 ×RPM+b 3 ×a+b 4 ×P+b 5 ×N; Where X represents the communication rate; b 0 represents the basic communication rate; M represents the driving mode; b 1 It represents the impact of driving mode on communication rate; RPM represents the speed of the motor; a represents the acceleration of the motor; P represents the power of the motor; N represents the energy consumption of the motor; b 2 , b 3 , b 4 , b 5 Expressed as weight coefficient; In urban driving mode, the vehicle frequently starts and stops during urban driving, requiring a higher communication rate to ensure the effective transmission of real-time data; In highway driving mode, the vehicle travels at a relatively stable speed on the highway, and the communication rate is appropriately reduced to save energy consumption of the motor.

[0012] According to the above scheme, in step S4: The collected data is organized into a data packet format, which includes header information and a payload; the header information includes a data type and a timestamp; the payload includes the motor's speed, current, voltage, torque, acceleration, power, and energy consumption; Generate a cyclic redundancy check code for the payload of the data packet using a cyclic redundancy check algorithm, and append the generated cyclic redundancy check code to the end of the data packet to form a complete data packet; The packaged complete data packet is sent to the motor controller via the communication bus; After receiving the complete data packet, the motor controller reads the effective load and the attached cyclic redundancy check code in the complete data packet; performs a cyclic redundancy check on the received effective load number, generates a cyclic redundancy check code of the received complete data packet, and compares it with the attached cyclic redundancy check code; When the two cyclic redundancy check codes match, it means that no errors occurred during the data transmission process, the data in the complete data packet is accurate and reliable, and the motor controller can trust and process the data; When the two cyclic redundancy check codes do not match, it means that an error occurred during data transmission, and the motor controller requests to send the data packet again to ensure the accuracy and reliability of the data; After the complete data packet is successfully received and no errors occur during transmission, the motor controller sends an acknowledgment signal to the motor sensor, indicating that the data packet has been received.

[0013] According to the above scheme, in step S5: A timer is set in the motor controller to record the time interval of each data transmission; the timer records the current time and stops timing when the next data frame is received; after receiving the data frame, the time interval between the previous and next data frames is calculated and stored; if the actual transmission time exceeds the average interval time, it is determined to be a delay; The baud rate is adjusted dynamically according to the minimum pulse width time. The formula is as follows: ; Where BR represents the baud rate; ΔT represents the time interval between data frames; Monitor the interval time between adjacent data frames and obtain the average interval time. The formula is as follows: ; Among them, T avg It is represented by the average interval time; Z is represented by the number of recorded frames; ΔT x Expressed as the time difference between the xth adjacent data frames; By comparing the average interval time with the time threshold, the communication address is automatically assigned to the motor sensor; when the data frame sent by the motor controller does not receive a reply from the motor sensor within the specified time, the communication is considered to have failed, and the address is reallocated to ensure the uniqueness and identifiability of each motor sensor.

[0014] According to the above solution, the working state of the motor includes the motor's speed, current, voltage and torque; the data transmission status includes communication success, delay and failure.

[0015] A data transmission system for motor adaptive control, the system comprising a motor controller, a motor sensor and a communication bus; The motor sensor is used to detect the working state of the motor and send the detected working state of the motor to the motor controller through the communication bus; The motor controller is responsible for sending a request to query the working status of the motor to the motor sensor through the communication bus, and receiving the working status of the motor collected by the motor sensor; after receiving the working status of the motor, performing a cyclic redundancy check to ensure the accuracy and reliability of data transmission; using a random forest model to identify the driving mode according to the working status of the motor collected by the motor sensor; obtaining a communication rate according to the identified driving mode; dynamically monitoring the working status of the motor and the data transmission, and adjusting the communication parameters according to the transmission delay; The communication bus is used to connect the motor controller and the motor sensor to transmit and receive data; The motor working state includes the motor speed, current, voltage and torque; The driving modes include urban driving mode and highway driving mode; the urban driving mode means that the motor needs frequent acceleration and deceleration, as well as a higher communication frequency; the highway driving mode means that the motor needs stable and continuous acceleration, needs to improve endurance, reduce motor energy consumption, and reduce communication rate.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. Through real-time data collection and processing, it can quickly respond to changes in different driving modes; 2. Automatically adjust the communication rate and control strategy based on the identified driving mode and motor status to optimize data transmission and motor performance; 3. Optimize motor operation and reduce energy consumption by real-time monitoring of motor power and energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flowchart of the steps of a data transmission method applied to motor adaptive control. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example: Figure 1 As shown, the present invention provides a technical solution, a data transmission method applied to motor adaptive control, the method comprising the steps of: The motor controller is connected to at least one motor sensor through a communication bus to form a unified bus system; the motor controller sends a query request to the motor sensor; the motor controller receives the working state of the motor returned by the motor sensor; the working state includes the speed, current, voltage and torque of the motor; Preprocessing the data collected by the motor sensor, the preprocessing including missing value processing, outlier detection and feature scaling; extracting feature data from the preprocessed data, the feature data including motor speed, current, voltage and torque; and constructing new features through the feature data, the new features including acceleration, power and energy consumption of the motor; Collected data: speed: 3000r / s; current: 50A; voltage: 400V; torque: 150Nm; The acceleration of the motor is expressed as the rate of change of the motor speed, and the formula is as follows: ; Where a is the acceleration of the motor; ΔRPM is the change in speed; Δt is the change in time; motor acceleration: 200RPM / s; The power of the motor is expressed as the output power of the motor, and the formula is as follows: P = J × RPM × 2π / 60; Among them, P represents the power of the motor; J represents the torque; RPM represents the speed; the power of the motor: P=J×RPM×2π / 60=157.08kW; The energy consumption of the motor is expressed as the electric energy consumed by the motor during operation, and the formula is as follows: N = I × U; Among them, N represents the energy consumption of the motor; I represents the current of the motor; U represents the voltage of the motor; the energy consumption of the motor: N=I×U=20kWh; Combine feature data and constructed new features into a dataset, and divide the dataset into a training set and a test set; The number of decision trees constructed is n; for each decision tree, a subset is extracted from the training set with replacement to form a new sample set; k features are randomly selected from the m features; among the selected k features, Gini impurity is used as an evaluation index, and the feature that minimizes the Gini impurity and its corresponding split point are selected as the splitting condition of the node to construct a decision tree; the Gini impurity is an indicator for evaluating the purity of the data set in the classification problem; The Gini impurity formula is as follows: ; Among them, Gini(p) represents the Gini impurity; k represents the total number of feature categories; p i It is expressed as the proportion of category i in the node; Use the training set data to train each tree to generate a random forest model; Use the test set to evaluate the model. For each test sample, use the random forest model to make predictions and obtain the prediction results of multiple decision trees. Vote for the prediction results of all decision trees and select the category with the most votes as the final prediction result. The formula is as follows: ; Among them, Y represents the prediction result; n represents the total number of decision trees; y j is the prediction result of the jth decision tree; Ⅱ is the indicator function; Ⅱ(y j =y i ) is expressed as the prediction result y for each decision tree j j , check whether it is equal to the currently considered category y i , if yes, then 1; if no, then 0; Predicting and identifying driving modes through a random forest model; the driving modes include urban driving modes and highway driving modes; In city driving, the vehicle starts and stops frequently, the motor speed changes greatly, the motor acceleration is high, and the motor energy consumption is high; in highway driving, the vehicle travels at a relatively stable speed, the motor speed changes less, the motor acceleration is low, and the motor energy consumption is relatively low.

[0020] According to the identified driving mode, the communication rate is calculated as follows: X=b 0 +b 1 ×M+b 2 ×RPM+b 3 ×a+b 4 ×P+b5 ×N; Where X represents the communication rate; b 0 represents the basic communication rate; M represents the driving mode; b 1 It represents the impact of driving mode on communication rate; RPM represents the speed of the motor; a represents the acceleration of the motor; P represents the power of the motor; N represents the energy consumption of the motor; b 2 , b 3 , b 4 , b 5 Expressed as weight coefficient; In urban driving mode, the vehicle frequently starts and stops during urban driving, requiring a higher communication rate to ensure the effective transmission of real-time data; In highway driving mode, the vehicle travels at a relatively stable speed on the highway, and the communication rate is appropriately reduced to save energy consumption of the motor.

[0021] The collected data is organized into a data packet format, which includes header information and a payload; the header information includes a data type and a timestamp; the payload includes the motor's speed, current, voltage, torque, acceleration, power, and energy consumption; Generate a cyclic redundancy check code for the payload of the data packet using a cyclic redundancy check algorithm, and append the generated cyclic redundancy check code to the end of the data packet to form a complete data packet; The packaged complete data packet is sent to the motor controller via the communication bus; After receiving the complete data packet, the motor controller reads the effective load and the attached cyclic redundancy check code in the complete data packet; performs a cyclic redundancy check on the received effective load number, generates a cyclic redundancy check code of the received complete data packet, and compares it with the attached cyclic redundancy check code; When the two cyclic redundancy check codes match, it means that no errors occurred during the data transmission process, the data in the complete data packet is accurate and reliable, and the motor controller can trust and process the data; When the two cyclic redundancy check codes do not match, it means that an error occurred during data transmission, and the motor controller requests to send the data packet again to ensure the accuracy and reliability of the data; After the complete data packet is successfully received and no errors occur during transmission, the motor controller sends an acknowledgment signal to the motor sensor, indicating that the data packet has been received.

[0022] A timer is set in the motor controller to record the time interval of each data transmission; the timer records the current time and stops timing when the next data frame is received; after receiving the data frame, the time interval between the previous and next data frames is calculated and stored; if the actual transmission time exceeds the average interval time, it is determined to be a delay; The baud rate is adjusted dynamically according to the minimum pulse width time. The formula is as follows: ; Wherein, BR represents the baud rate; ΔT represents the time interval between data frames.

[0023] Monitor the interval time between adjacent data frames and obtain the average interval time. The formula is as follows: ; Among them, T avg It is represented by the average interval time; Z is represented by the number of recorded frames; ΔT x Expressed as the time difference between the xth adjacent data frames; By comparing the average interval time with the time threshold, the communication address is automatically assigned to the motor sensor; when the data frame sent by the motor controller does not receive a reply from the motor sensor within the specified time, the communication is considered to have failed, and the address is reallocated to ensure the uniqueness and identifiability of each motor sensor.

[0024] The present invention provides another embodiment, a data transmission system for motor adaptive control, the system comprising a motor controller, a motor sensor and a communication bus; When the electric vehicle is in the city driving mode, the motor sensor detects the working state of the motor in real time; the working state includes the speed, current, voltage and torque of the motor; when the electric vehicle frequently accelerates and decelerates in the city, the motor sensor sends the working state of the motor to the motor controller through the communication bus; The motor controller receives the motor working status collected by the motor sensor through the communication bus; performs cyclic redundancy check to ensure the accuracy and reliability of data transmission; The random forest model is used to identify the driving mode according to the motor working status; the current driving mode is identified as urban driving mode, the communication frequency is calculated, and the communication frequency is increased to quickly respond to changes in driving status.

[0025] When the electric vehicle enters the highway, the electric vehicle is in the highway driving mode; the motor sensor detects the motor working state in real time; and sends the motor working state to the motor controller via the communication bus; The motor controller receives the motor working status collected by the motor sensor through the communication bus; performs cyclic redundancy check to ensure the accuracy and reliability of data transmission; The random forest model is used to identify driving modes based on the motor's operating status. The current driving mode is identified as urban, and the communication frequency is calculated to reduce the communication rate to save energy. At the same time, the motor output is adjusted to ensure stable acceleration and improve endurance.

[0026] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A data transmission method for motor adaptive control, characterized in that: The method comprises the steps of: S1, connecting the motor controller and the motor sensor through a communication bus to form a unified communication mechanism; S2. Preprocess the data collected by the motor sensor, extract feature data, and construct new features through the feature data; use the random forest model to identify the driving mode; S3, calculating the communication rate according to the driving pattern, feature data and new features identified by the random forest model; S4, using cyclic redundancy check to generate a check code, appending it to the end of the data packet and sending it to the motor controller; the motor controller receives the data packet and verifies the accuracy of the data; S5. Dynamically adjust the communication rate and monitor the working status of the motor and the data transmission status during the data transmission process.

2. The data transmission method for motor adaptive control according to claim 1, characterized in that: In step S1: The motor controller is connected to at least one motor sensor through a communication bus to form a unified bus system; the motor controller sends a query request to the motor sensor; the motor controller receives the working status of the motor returned by the motor sensor; the working status includes the motor's speed, current, voltage and torque.

3. The data transmission method for motor adaptive control according to claim 1, characterized in that: In step S2: Preprocessing the collected data, including missing value processing, outlier detection and feature scaling; extracting feature data from the preprocessed data, including motor speed, current, voltage and torque; and constructing new features through the feature data, including motor acceleration, power and energy consumption; Combine feature data and constructed new features into a dataset, and divide the dataset into a training set and a test set; A random forest model is constructed, and a driving mode is predicted and identified through the random forest model; the driving mode includes an urban driving mode and a highway driving mode.

4. The data transmission method for motor adaptive control according to claim 3, characterized in that: The acceleration of the motor is expressed as the rate of change of the motor speed, and the formula is as follows: ； Where a represents the acceleration of the motor; ΔRPM represents the change in speed; Δt represents the change in time; The power of the motor is expressed as the output power of the motor, and the formula is as follows: P = J × RPM × 2π / 60; Among them, P represents the power of the motor; J represents the torque; RPM represents the speed; The energy consumption of the motor is expressed as the electric energy consumed by the motor during operation, and the formula is as follows: N = I × U; Among them, N represents the electric energy of the motor; I represents the current of the motor; U represents the voltage of the motor.

5. The data transmission method for motor adaptive control according to claim 3, characterized in that: The number of decision trees constructed is n; for each decision tree, a subset is extracted from the training set with replacement to form a new sample set; k features are randomly selected from the m features; among the selected k features, Gini impurity is used as an evaluation index, and the feature that minimizes the Gini impurity and its corresponding split point are selected as the splitting condition of the node to construct a decision tree; the Gini impurity is an indicator for evaluating the purity of the data set in the classification problem; The Gini impurity formula is as follows: ； Among them, Gini(p) represents the Gini impurity; k represents the total number of feature categories; p i It is expressed as the proportion of category i in the node; Use the training set data to train each tree to generate a random forest model; Use the test set to evaluate the model. For each test sample, use the random forest model to make predictions and obtain the prediction results of multiple decision trees. Vote for the prediction results of all decision trees and select the category with the most votes as the final prediction result. The formula is as follows: ； Among them, Y represents the prediction result; n represents the total number of decision trees; y j is the prediction result of the jth decision tree; Ⅱ is the indicator function; Ⅱ(y j =y i ) is expressed as the prediction result y for each decision tree j j , check whether it is equal to the currently considered category y i , if yes, then 1; if no, then 0.

6. The data transmission method for motor adaptive control according to claim 1, characterized in that: In step S3: According to the identified driving mode, the communication rate is calculated as follows: X=b0+b1×M+b2×RPM+b3×a+b4×P+b5×N; Among them, X represents the communication rate; b0 represents the basic communication rate; M represents the driving mode; b1 represents the impact of the driving mode on the communication rate; RPM represents the speed of the motor; a represents the acceleration of the motor; P represents the power of the motor; N represents the energy consumption of the motor; b2, b3, b4, and b5 represent weight coefficients.

7. The data transmission method for motor adaptive control according to claim 1, characterized in that: In step S4: The collected data is organized into a data packet format, which includes header information and a payload; the header information includes a data type and a timestamp; the payload includes the motor's speed, current, voltage, torque, acceleration, power, and energy consumption; Generate a cyclic redundancy check code for the payload of the data packet using a cyclic redundancy check algorithm, and append the generated cyclic redundancy check code to the end of the data packet to form a complete data packet; The packaged complete data packet is sent to the motor controller via the communication bus; After receiving the complete data packet, the motor controller reads the effective load and the attached cyclic redundancy check code in the complete data packet; performs a cyclic redundancy check on the received effective load number, generates a cyclic redundancy check code of the received complete data packet, and compares it with the attached cyclic redundancy check code; When the two cyclic redundancy check codes match, it means that no errors occurred during the data transmission process, the data in the complete data packet is accurate and reliable, and the motor controller can trust and process the data; When the two cyclic redundancy check codes do not match, it means that an error occurred during data transmission, and the motor controller requests to send the data packet again to ensure the accuracy and reliability of the data; After the complete data packet is successfully received and no errors occur during transmission, the motor controller sends an acknowledgment signal to the motor sensor, indicating that the data packet has been received.

8. The data transmission method for motor adaptive control according to claim 1, characterized in that: In step S5: A timer is set in the motor controller to record the time interval of each data transmission; the timer records the current time and stops timing when the next data frame is received; after receiving the data frame, the time interval between the previous and next data frames is calculated and stored; if the actual transmission time exceeds the average interval time, it is determined to be a delay; The baud rate is adjusted dynamically according to the minimum pulse width time. The formula is as follows: ； Where BR represents the baud rate; ΔT represents the time interval between data frames; Monitor the interval time between adjacent data frames and obtain the average interval time. The formula is as follows: ； Among them, T avg It is represented by the average interval time; Z is represented by the number of recorded frames; ΔT x Expressed as the time difference between the xth adjacent data frames; By comparing the average interval time with the time threshold, the communication address is automatically assigned to the motor sensor; when the data frame sent by the motor controller does not receive a reply from the motor sensor within the specified time, the communication is considered to have failed, and the address is reallocated to ensure the uniqueness and identifiability of each motor sensor.

9. The data transmission method for motor adaptive control according to claim 1, characterized in that: The working state of the motor includes the motor's speed, current, voltage and torque; the data transmission status includes communication success, delay and failure.

10. A data transmission system for motor adaptive control, characterized in that: The system includes a motor controller, a motor sensor, and a communication bus; The motor sensor is used to detect the working state of the motor and send the detected working state of the motor to the motor controller through the communication bus; The motor controller is responsible for sending a request to query the working status of the motor to the motor sensor through the communication bus, and receiving the working status of the motor collected by the motor sensor; after receiving the working status of the motor, a cyclic redundancy check is performed to ensure the accuracy and reliability of data transmission; Based on the working state of the motor collected by the motor sensor, the driving mode is identified using the random forest model; the communication rate is obtained based on the identified driving mode; the working state of the motor and the data transmission are dynamically monitored, and the communication parameters are adjusted according to the transmission delay; The communication bus is used to connect the motor controller and the motor sensor to transmit and receive data; The motor working state includes the motor speed, current, voltage and torque; The driving modes include a city driving mode and a highway driving mode; the city driving mode means that the motor needs frequent acceleration and deceleration, as well as a higher communication frequency; The highway driving mode means that the motor needs to be stable and continuously accelerated, the cruising range needs to be improved, the motor energy consumption needs to be reduced, and the communication rate needs to be reduced.

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