New energy automobile driving motor safety management system and method based on intelligent control

Abstract

The invention discloses a new energy automobile driving motor safety management system and method based on intelligent control, particularly relates to the technical field of driving motors, and provides an important basis for evaluating mechanical interaction between motors by obtaining mechanical transmission coupling information to calculate a mechanical transmission coupling coefficient; electrical coupling coefficients are calculated by acquiring electrical coupling information among the motors in the multi-motor driving system, transmission and influence of electrical signals among the motors are further revealed, and abnormity in an electrical system is recognized; control coupling information among motors in a multi-motor driving system is obtained to calculate a control coupling coefficient to quantify the coupling degree of motor control signals, cooperative control behaviors among the motors are determined, each motor provides independent fault information, and a mechanical transmission coupling coefficient, an electrical coupling coefficient and the control coupling coefficient are synthesized to realize cooperative control of the motors. A single-point cooperative fault discrimination model is constructed, and a single-point motor fault and a system cooperative fault can be effectively distinguished.

Description

Technical Field

[0001] The present invention relates to the technical field of drive motors, and more specifically, to a safety management system and method for drive motors of new energy vehicles based on intelligent control. Background Art

[0002] With the continuous development of new energy vehicle technology, especially the increasing popularity of electric vehicles, multi-motor drive systems, as one of their key technologies, have been widely adopted in new energy vehicles to enhance driving performance, increase system redundancy, and improve energy efficiency. Multi-motor drive systems optimize power output and achieve more precise control by integrating multiple motors, thereby providing a smoother and more efficient driving experience. However, as system complexity increases, ensuring the reliability and safety of multi-motor drive systems has become a major challenge in the new energy vehicle industry.

[0003] Fault diagnosis is particularly important in multi-motor drive systems. Traditional single-motor fault diagnosis methods are often difficult to effectively apply to multi-motor systems because these systems typically operate in highly coupled states. A single motor failure or anomaly can affect the power distribution and coordinated operation of the entire system. System coordination issues (such as imbalance or energy distribution problems between motors) can also masquerade as single-motor failures. This complicates the task of fault diagnosis, and traditional fault detection methods may not be effective in these systems. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a new energy vehicle drive motor safety management system and method based on intelligent control to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A new energy vehicle drive motor safety management method based on intelligent control includes the following steps: Step S1 is used to obtain mechanical transmission coupling information between motors in a multi-motor drive system, and calculate a mechanical transmission coupling coefficient based on the mechanical transmission coupling information to evaluate the degree of mechanical coupling influence between the multiple motors; Step S2 is used to obtain electrical coupling information between motors in the multi-motor drive system, and calculate the electrical coupling coefficient based on the electrical coupling information to evaluate the degree of electrical coupling influence between the multiple motors; Step S3 is used to obtain control coupling information between motors in the multi-motor drive system, and calculate the control coupling coefficient based on the control coupling information to evaluate the control coupling influence degree between the multiple motors; Step S4: construct a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, output a single-point collaborative fault identification index, and determine whether the abnormal mode identified by the existing fault detection method is a single-point motor fault or a system collaborative fault.

[0006] In a preferred embodiment, by acquiring mechanical transmission coupling information between motors in a multi-motor drive system, analyzing the interaction and mechanical coupling degree of each motor in the transmission system, and obtaining a mechanical transmission coupling coefficient, the interaction and mechanical coupling degree of each motor in the transmission system are measured; The logic for obtaining the mechanical transmission coupling coefficient is as follows: Obtaining the actual speed, actual torque, and vibration signals of key nodes of each motor, including but not limited to gears and couplings; Calculate the motor speed coupling according to the actual motor speed , the expression is as follows ,in Indicates the The actual speed of the motor, , is a positive integer; Calculate the motor torque coupling based on the actual torque of the motor , the expression is as follows ,in Indicates the The actual torque of each motor; Calculate the vibration coupling degree based on the vibration signals of the motor's key nodes , the expression is as follows ,in Indicates the Vibration signal of a motor; Calculate the mechanical transmission coupling coefficient , the expression is as follows ,in Respectively represent the preset proportional coefficients of motor speed coupling, motor torque coupling, and vibration coupling, and Both are greater than 0.

[0007] In a preferred embodiment, the electrical coupling information between the motors in the multi-motor drive system is obtained, the electrical interaction and the degree of electrical coupling between the motors are analyzed, and the electrical coupling coefficient is obtained to measure the electrical interaction and the degree of electrical coupling between the motors; The logic for obtaining the electrical coupling coefficient is as follows: Obtain electrical operating parameters of each motor, including but not limited to motor voltage and motor current; Calculate the electrical coupling between the nth motor and the mth motor , the calculation expression is as follows ,in represents the covariance of the voltages of the nth motor and the mth motor, represents the covariance of the current of the nth motor and the mth motor, represents the standard deviation of the voltage of the nth motor, represents the standard deviation of the voltage of the mth motor, represents the standard deviation of the current of the nth motor, represents the standard deviation of the current of the mth motor; An electrical coupling matrix is ​​constructed by taking the electrical coupling degrees of the nth motor and the mth motor as matrix elements; Calculating the electrical coupling coefficient , the expression is as follows ,in Indicates the electrical coupling between the nth motor and the mth motor, Represents the total number of elements in the electrical coupling matrix.

[0008] In a preferred embodiment, the control coupling degree between the motors in the multi-motor drive system is analyzed by using the control coupling information between the motors, and the control coupling coefficient is obtained to measure the control coupling degree between the motors; The logic for obtaining the control coupling coefficient is as follows: Obtain the control signals of each motor and calculate the Pearson correlation coefficient of the control signals between motors , the expression is as follows ,in represents the covariance of the control signals of the u-th motor and the v-th motor, represents the standard deviation of the control signal of the u-th motor, The table shows the standard deviation of the control signal of the vth motor; The first control coupling degree is calculated based on the Pearson correlation coefficient of the control signal between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the cross spectral density of the control signals between the motors , the expression is as follows ,in represents the control signal of the u-th motor, It represents the complex conjugate of the control signal of the vth motor after time delay shift. The time lag refers to the signal phase difference between motor u and motor v, j represents the imaginary unit, Indicates frequency, Representation of time lag The integration time range; The second control coupling degree is calculated based on the cross spectral density of the control signals between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the control coupling coefficient , the expression is as follows ,in represent the preset proportional coefficients of the first control coupling degree and the second control coupling degree, respectively, and Both are greater than 0.

[0009] In a preferred embodiment, a single-point collaborative fault identification model is constructed based on the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, and a single-point collaborative fault identification index is output. The model is based on the following formula , where Respectively represent the preset proportional coefficients of mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, and Both are greater than 0.

[0010] In a preferred embodiment, the single-point collaborative fault discrimination index is compared with a preset single-point collaborative fault discrimination index threshold to determine whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault, as follows: If the single-point collaborative fault identification index is greater than the single-point collaborative fault identification index threshold, a single-point fault signal is generated; If the single-point collaborative fault identification index is less than or equal to the single-point collaborative fault identification index threshold, a system collaborative fault signal is generated.

[0011] In a preferred embodiment, the new energy vehicle drive motor safety management system based on intelligent control includes a mechanical coupling module, an electrical coupling module, a control coupling module, and a screening and evaluation module; The mechanical coupling module is used to obtain the mechanical transmission coupling information between motors in a multi-motor drive system, calculate the mechanical transmission coupling coefficient based on the mechanical transmission coupling information, and evaluate the degree of mechanical coupling influence between multiple motors; The electrical coupling module is used to obtain the electrical coupling information between motors in a multi-motor drive system, calculate the electrical coupling coefficient based on the electrical coupling information, and evaluate the degree of electrical coupling impact between multiple motors; The control coupling module is used to obtain the control coupling information between motors in the multi-motor drive system, calculate the control coupling coefficient based on the control coupling information, and evaluate the control coupling influence between multiple motors; The identification and evaluation module constructs a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, outputs a single-point collaborative fault identification index, and determines whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault.

[0012] The technical effects and advantages of the present invention are as follows: The present invention obtains mechanical transmission coupling information to calculate the mechanical transmission coupling coefficient, providing an important basis for evaluating mechanical interactions between motors. It also obtains electrical coupling information between motors in a multi-motor drive system to calculate the electrical coupling coefficient, further revealing the transmission and influence of electrical signals between motors and helping to identify anomalies in the electrical system. It obtains control coupling information between motors in the multi-motor drive system to calculate the control coupling coefficient, quantifying the degree of coupling of motor control signals and clarifying the coordinated control behavior between motors. Each motor provides independent fault information. By integrating the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, a single-point coordinated fault identification model is constructed, which can effectively distinguish between single-point motor faults and system coordinated faults. In multi-motor systems, especially when facing complex fault modes, it can provide more accurate fault type judgment. By outputting a single-point coordinated fault identification index, it can help existing fault detection methods more accurately identify abnormal modes in the system, thereby avoiding misjudgments caused by single-point faults or hidden dangers caused by system coordinated faults. While improving fault diagnosis accuracy, it also enhances the fault tolerance of the multi-motor drive system, avoids paralysis of the entire system due to individual motor failures, and ensures system redundancy and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a flow chart of the method of Example 1 of the present invention; Figure 2 This is a flow chart of the system of Example 2 of the present invention. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0015] Example 1: Figure 1 The present invention provides a new energy vehicle drive motor safety management method based on intelligent control, which includes the following steps: Step S1 is used to obtain mechanical transmission coupling information between motors in a multi-motor drive system, and calculate a mechanical transmission coupling coefficient based on the mechanical transmission coupling information to evaluate the degree of mechanical coupling influence between the multiple motors; Step S2 is used to obtain electrical coupling information between motors in the multi-motor drive system, and calculate the electrical coupling coefficient based on the electrical coupling information to evaluate the degree of electrical coupling influence between the multiple motors; Step S3 is used to obtain control coupling information between motors in the multi-motor drive system, and calculate the control coupling coefficient based on the control coupling information to evaluate the control coupling influence degree between the multiple motors; Step S4: constructing a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, outputting a single-point collaborative fault identification index, and determining whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault; Step S1 is used to obtain mechanical transmission coupling information between motors in a multi-motor drive system, and calculate a mechanical transmission coupling coefficient based on the mechanical transmission coupling information to evaluate the degree of mechanical coupling influence between the multiple motors; The mechanical transmission coupling coefficient is used to measure the degree of interaction and coupling between the motors in the transmission system, reflecting the power transmission efficiency, mechanical connection status, and load sharing between the motors. By acquiring and analyzing the mechanical transmission coupling information in the multi-motor drive system in real time and calculating the mechanical transmission coupling coefficient, the power transmission and collaborative working status between the motors can be quantified. When the mechanical transmission coupling coefficient is high, that is, the coupling is good, the anomaly usually comes from the independent failure of a single motor; when the mechanical transmission coupling coefficient is low, it indicates that there is a strong mutual influence between the motors or mechanical transmission anomalies, which may be a system collaborative failure. This method can overcome the problem of poor adaptability of traditional fault diagnosis methods to multi-motor systems. It not only improves the accuracy of fault mode identification, but also provides a clear direction for further optimizing fault handling strategies, thereby improving the reliability and safety of multi-motor drive systems.

[0016] Therefore, by obtaining the mechanical transmission coupling information between the motors in the multi-motor drive system, the interaction and mechanical coupling degree of each motor in the transmission system are analyzed, and the mechanical transmission coupling coefficient is obtained to measure the interaction and mechanical coupling degree of each motor in the transmission system; The logic for obtaining the mechanical transmission coupling coefficient is as follows: Obtaining the actual speed, actual torque, and vibration signals of key nodes of each motor, including but not limited to gears and couplings; It should be noted that the actual speed, actual torque and vibration signals of key nodes of each motor can be obtained in real time by installing high-precision sensors at different parts of the motor. For example, a Hall sensor can be installed on the motor rotor to collect the actual speed of the motor, a torque sensor can be installed on the motor shaft to collect the actual torque, and vibration sensors can be installed on the gears, couplings and other components of the motor to collect the vibration signals of key nodes. Calculate the motor speed coupling according to the actual motor speed , the expression is as follows ,in Indicates the The actual speed of the motor, , is a positive integer; Calculate the motor torque coupling based on the actual torque of the motor , the expression is as follows ,in Indicates the The actual torque of each motor; Calculate the vibration coupling degree based on the vibration signals of the motor's key nodes , the expression is as follows ,in Indicates the Vibration signal of a motor; Calculate the mechanical transmission coupling coefficient , the expression is as follows ,in Respectively represent the preset proportional coefficients of motor speed coupling, motor torque coupling, and vibration coupling, and All greater than 0; It should be noted that before calculating the mechanical transmission coupling coefficient, it is necessary to ensure that the motor speed coupling, motor torque coupling, and vibration coupling are all normalized; Set it according to the actual situation. For example, adopt the expert empowerment method, that is, invite experts in relevant fields to determine the preset proportion coefficients of various indicators through professional opinion surveys and comprehensive evaluations; Step S2 is used to obtain electrical coupling information between motors in the multi-motor drive system, and calculate the electrical coupling coefficient based on the electrical coupling information to evaluate the degree of electrical coupling influence between the multiple motors; The electrical coupling coefficient is a key metric used to measure the degree of electrical interaction and coordination between motors in a multi-motor drive system. In a multi-motor system, motors not only transmit torque through mechanical coupling but also share power and control signals through electrical coupling. The calculation of the electrical coupling coefficient takes into account the interdependencies of electrical parameters such as current, voltage, and load between motors, effectively capturing the dynamic changes in electrical transmission between motors. When a system fault occurs, the electrical coupling coefficient can help determine whether the fault is a single motor fault or a systemic fault caused by electrical coordination issues between multiple motors. A low electrical coupling coefficient indicates weak electrical dependencies between motors, making the system anomaly more likely to be caused by a single motor failure. Conversely, a high electrical coupling coefficient indicates closer electrical connections between motors, and a single motor failure could significantly alter the electrical behavior of the entire system, leading to a coordinated failure. Therefore, analysis of the electrical coupling coefficient can more accurately determine whether the anomaly is a single motor failure or a coordinated system failure. Quantifying the electrical coupling coefficient can better assess the root cause of the fault, avoid unnecessary repairs or adjustments due to incorrect fault mode determination, and ultimately improve system reliability and safety. This process not only improves the accuracy of fault diagnosis but also allows for quick identification of local or systemic issues when electrical anomalies occur in the system, enabling more targeted diagnostic and treatment measures and reducing the risk of misdiagnosis and system downtime. Therefore, by obtaining the electrical coupling information between the motors in the multi-motor drive system, the electrical interaction and electrical coupling degree between the motors are analyzed, and the electrical coupling coefficient is obtained to measure the electrical interaction and electrical coupling degree between the motors; The logic for obtaining the electrical coupling coefficient is as follows: Obtain electrical operating parameters of each motor, including but not limited to motor voltage and motor current; Calculate the electrical coupling between the nth motor and the mth motor , the calculation expression is as follows ,in represents the covariance of the voltages of the nth motor and the mth motor, represents the covariance of the current of the nth motor and the mth motor, represents the standard deviation of the voltage of the nth motor, represents the standard deviation of the voltage of the mth motor, represents the standard deviation of the current of the nth motor, represents the standard deviation of the current of the mth motor; An electrical coupling matrix is ​​constructed by taking the electrical coupling degrees of the nth motor and the mth motor as matrix elements; Calculating the electrical coupling coefficient , the expression is as follows ,in Indicates the electrical coupling between the nth motor and the mth motor, represents the total number of elements in the electrical coupling matrix; Step S3 is used to obtain control coupling information between motors in the multi-motor drive system, and calculate the control coupling coefficient based on the control coupling information to evaluate the control coupling influence degree between the multiple motors; The control coupling coefficient measures the degree of coupling between motor control strategies and reflects the degree of mutual influence between multiple motors through the control system. In a multi-motor drive system, each motor is typically coordinated through shared control signals (such as reference voltage and speed control signals). The control coupling coefficient characterizes the control interactions between these motors. A high control coupling coefficient indicates strong correlation between the control signals between the motors, indicating a high degree of system synergy. A low control coupling coefficient, on the other hand, indicates strong independence between the control signals between the motors, making each motor in the system relatively independent and more likely to be caused by a single-point motor failure. In the event of a single-point failure, the control signal of the faulty motor may deviate significantly from that of the other motors, resulting in a decrease in the control coupling coefficient, while the other motors maintain normal operation. Analysis methods based on the control coupling coefficient can effectively determine whether the abnormal pattern identified by existing fault detection methods is a single-point motor failure or a system-coordinated failure. In a multi-motor drive system, each motor typically coordinates through control signals to optimize system performance. However, when a fault occurs, the control coupling relationship between the motors changes, reflecting the nature of the fault. In the event of a system-coordinated failure, the control signals of multiple motors will exhibit a consistent abnormal pattern. Therefore, by calculating and analyzing the control coupling coefficient, single-point faults and system collaborative faults can be effectively distinguished, helping existing fault detection methods provide more accurate fault type judgments, avoiding confusion between systemic faults and single-point faults, and improving the accuracy and reliability of fault diagnosis.

[0017] Therefore, the control coupling information between motors in the multi-motor drive system is used to analyze the control coupling degree between each motor and obtain the control coupling coefficient to measure the control coupling degree between each motor; The logic for obtaining the control coupling coefficient is as follows: Obtain the control signals of each motor and calculate the Pearson correlation coefficient of the control signals between motors , the expression is as follows ,in represents the covariance of the control signals of the u-th motor and the v-th motor, represents the standard deviation of the control signal of the u-th motor, represents the standard deviation of the control signal of the vth motor; The first control coupling degree is calculated based on the Pearson correlation coefficient of the control signal between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the cross spectral density of the control signals between the motors , the expression is as follows ,in represents the control signal of the u-th motor, It represents the complex conjugate of the control signal of the vth motor after time delay shift. The time lag refers to the signal phase difference between motor u and motor v, j represents the imaginary unit, Indicates frequency, Representation of time lag The integration time range; The second control coupling degree is calculated based on the cross spectral density of the control signals between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the control coupling coefficient , the expression is as follows ,in represent the preset proportional coefficients of the first control coupling degree and the second control coupling degree, respectively, and All greater than 0; It should be noted that before calculating the control coupling coefficient, it is necessary to ensure that the first control coupling degree and the second control coupling degree are normalized; It is set according to actual conditions. For example, the expert empowerment method is adopted, that is, experts in relevant fields are invited to determine the preset proportion coefficients of various indicators through professional opinion surveys and comprehensive evaluations.

[0018] Step S4: constructing a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, outputting a single-point collaborative fault identification index, and determining whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault; A single-point collaborative fault identification model is constructed based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, and a single-point collaborative fault identification index is output. The model is based on the following formula , where Respectively represent the preset proportional coefficients of mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, and All greater than 0; It should be noted that before building the single-point collaborative fault identification model, it is necessary to ensure that the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient are all normalized; Set it according to the actual situation. For example, adopt the expert empowerment method, that is, invite experts in relevant fields to determine the preset proportion coefficients of various indicators through professional opinion surveys and comprehensive evaluations; From the above calculation expression, it can be seen that the larger the mechanical transmission coupling coefficient, the smaller the electrical coupling coefficient, and the smaller the control coupling coefficient, the larger the single-point collaborative fault identification index, indicating that the probability that the abnormal mode identified by the existing fault detection method is a single-point motor fault is greater. Conversely, the smaller the mechanical transmission coupling coefficient, the larger the electrical coupling coefficient, and the larger the control coupling coefficient, the smaller the single-point collaborative fault identification index, indicating that the probability that the abnormal mode identified by the existing fault detection method is a system collaborative fault is greater. The single-point collaborative fault discrimination index is compared with the preset single-point collaborative fault discrimination index threshold to determine whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault, as follows: If the single-point collaborative fault discrimination index is greater than the single-point collaborative fault discrimination index threshold, it indicates that the abnormal pattern identified by the existing fault detection method is a single-point motor fault, and a single-point fault signal is generated; If the single-point collaborative fault discrimination index is less than or equal to the single-point collaborative fault discrimination index threshold, it indicates that the abnormal pattern identified by the existing fault detection method is a system collaborative fault, and a system collaborative fault signal is generated.

[0019] The present invention obtains mechanical transmission coupling information to calculate the mechanical transmission coupling coefficient, providing an important basis for evaluating mechanical interactions between motors. It also obtains electrical coupling information between motors in a multi-motor drive system to calculate the electrical coupling coefficient, further revealing the transmission and influence of electrical signals between motors and helping to identify anomalies in the electrical system. It obtains control coupling information between motors in the multi-motor drive system to calculate the control coupling coefficient, quantifying the degree of coupling of motor control signals and clarifying the coordinated control behavior between motors. Each motor provides independent fault information. By integrating the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, a single-point coordinated fault identification model is constructed, which can effectively distinguish between single-point motor faults and system coordinated faults. In multi-motor systems, especially when facing complex fault modes, it can provide more accurate fault type judgment. By outputting a single-point coordinated fault identification index, it can help existing fault detection methods more accurately identify abnormal modes in the system, thereby avoiding misjudgments caused by single-point faults or hidden dangers caused by system coordinated faults. While improving fault diagnosis accuracy, it also enhances the fault tolerance of the multi-motor drive system, avoids paralysis of the entire system due to individual motor failures, and ensures system redundancy and reliability.

[0020] Example 2: This example is an introduction to the safety management system of the new energy vehicle drive motor based on intelligent control. Figure 2 As shown, it includes a mechanical coupling module, an electrical coupling module, a control coupling module, and a screening and evaluation module; The mechanical coupling module is used to obtain the mechanical transmission coupling information between motors in a multi-motor drive system, calculate the mechanical transmission coupling coefficient based on the mechanical transmission coupling information, and evaluate the degree of mechanical coupling influence between multiple motors; The electrical coupling module is used to obtain the electrical coupling information between motors in a multi-motor drive system, calculate the electrical coupling coefficient based on the electrical coupling information, and evaluate the degree of electrical coupling impact between multiple motors; The control coupling module is used to obtain the control coupling information between motors in the multi-motor drive system, calculate the control coupling coefficient based on the control coupling information, and evaluate the control coupling influence between multiple motors; The identification and evaluation module constructs a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, outputs a single-point collaborative fault identification index, and determines whether the abnormal pattern identified by the existing fault detection method is a single-point motor fault or a system collaborative fault.

[0021] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0022] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0023] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0024] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the system and method described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0025] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways.

[0026] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A new energy vehicle drive motor safety management method based on intelligent control, characterized in that: The steps include: Step S1 is used to obtain mechanical transmission coupling information between motors in a multi-motor drive system, and calculate a mechanical transmission coupling coefficient based on the mechanical transmission coupling information to evaluate the influence of mechanical coupling between the multiple motors; Step S2 is used to obtain electrical coupling information between motors in a multi-motor drive system, and calculate an electrical coupling coefficient based on the electrical coupling information to evaluate the degree of electrical coupling influence between the multiple motors; Step S3, for obtaining control coupling information between motors in the multi-motor drive system, and calculating a control coupling coefficient according to the control coupling information, and evaluating the control coupling influence degree between the multi-motor; Step S4, constructing a single-point collaborative fault identification model according to the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, outputting a single-point collaborative fault identification index, and determining whether the abnormal mode identified by the existing fault detection method is a single-point motor fault or a system collaborative fault.

2. The method for safety management of driving motors of new energy vehicles based on intelligent control according to claim 1 is characterized in that: By obtaining the mechanical transmission coupling information between motors in the multi-motor drive system, the interaction and mechanical coupling degree of each motor in the transmission system are analyzed, and the mechanical transmission coupling coefficient is obtained to measure the interaction and mechanical coupling degree of each motor in the transmission system; The logic for obtaining the mechanical transmission coupling coefficient is as follows: Obtaining the actual speed, actual torque and vibration signals of key nodes of each motor, wherein the key nodes include but are not limited to gears and couplings; Calculate the motor speed coupling according to the actual motor speed , the expression is as follows: ,in Indicates The actual speed of the motor, , is a positive integer; Calculate the motor torque coupling based on the actual torque of the motor , the expression is as follows: ,in Indicates The actual torque of each motor; Calculate the vibration coupling degree based on the vibration signals of the motor key nodes , the expression is as follows ,in Indicates The vibration signal of a motor; Calculate the mechanical transmission coupling coefficient , the expression is as follows ,in Respectively represent the preset proportional coefficients of motor speed coupling, motor torque coupling, and vibration coupling, and Both are greater than 0.

3. The method for safety management of new energy vehicle drive motor based on intelligent control according to claim 1 is characterized in that: By acquiring the electrical coupling information between motors in a multi-motor drive system, the electrical interaction and electrical coupling degree between the motors are analyzed, and the electrical coupling coefficient is obtained to measure the electrical interaction and electrical coupling degree between the motors; The logic for obtaining the electrical coupling coefficient is as follows: Obtain electrical operating parameters of each motor, including but not limited to motor voltage and motor current; Calculate the electrical coupling between the nth motor and the mth motor , the calculation expression is as follows ,in represents the covariance of the voltages of the nth motor and the mth motor, represents the covariance of the current of the nth motor and the mth motor, represents the standard deviation of the voltage of the nth motor, represents the standard deviation of the voltage of the mth motor, represents the standard deviation of the current of the nth motor, represents the standard deviation of the current of the mth motor; An electrical coupling matrix is ​​constructed by using the electrical coupling degrees of the nth motor and the mth motor as matrix elements; Calculating the electrical coupling coefficient , the expression is as follows ,in represents the electrical coupling between the nth motor and the mth motor, Represents the total number of elements in the electrical coupling matrix.

4. The method for safety management of new energy vehicle drive motor based on intelligent control according to claim 1 is characterized in that: By using the control coupling information between motors in the multi-motor drive system, the control coupling degree between the motors is analyzed, and the control coupling coefficient is obtained to measure the control coupling degree between the motors; The logic for obtaining the control coupling coefficient is as follows: Obtain the control signals of each motor and calculate the Pearson correlation coefficient of the control signals between motors , the expression is as follows ,in represents the covariance of the control signals of the u-th motor and the v-th motor, represents the standard deviation of the control signal of the u-th motor, represents the standard deviation of the control signal of the vth motor; The first control coupling degree is calculated based on the Pearson correlation coefficient of the control signal between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the cross spectral density of the control signals between the motors , the expression is as follows ,in represents the control signal of the u-th motor, It means that the control signal of the vth motor is complex conjugate after time delay shift. The time lag refers to the signal phase difference between motor u and motor v, j represents the imaginary unit, Indicates frequency, Indicates time lag The integration time range of The second control coupling degree is calculated based on the cross-spectral density of the control signals between the motors , the expression is as follows ,in Indicates the total number of motors; Calculate the control coupling coefficient , the expression is as follows ,in represent the preset proportional coefficients of the first control coupling degree and the second control coupling degree, respectively, and Both are greater than 0.

5. The method for safety management of new energy vehicle drive motor based on intelligent control according to claim 1 is characterized in that: A single-point collaborative fault identification model is constructed based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, and a single-point collaborative fault identification index is output. The model is based on the following formula , where Respectively represent the preset proportional coefficients of the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, and Both are greater than 0.

6. The method for safety management of driving motors of new energy vehicles based on intelligent control according to claim 5 is characterized in that: The single-point collaborative fault identification index is compared with the preset single-point collaborative fault identification index threshold to determine whether the abnormal mode identified by the existing fault detection method is a single-point motor fault or a system collaborative fault, as follows: If the single-point collaborative fault discrimination index is greater than the single-point collaborative fault discrimination index threshold, a single-point fault signal is generated; If the single-point collaborative fault identification index is less than or equal to the single-point collaborative fault identification index threshold, a system collaborative fault signal is generated.

7. A new energy vehicle drive motor safety management system based on intelligent control, used to implement the new energy vehicle drive motor safety management method based on intelligent control as described in any one of claims 1 to 6, characterized in that: Including mechanical coupling module, electrical coupling module, control coupling module, and identification and evaluation module; The mechanical coupling module is used to obtain the mechanical transmission coupling information between motors in the multi-motor drive system, calculate the mechanical transmission coupling coefficient based on the mechanical transmission coupling information, and evaluate the influence of mechanical coupling between multiple motors; The electrical coupling module is used to obtain the electrical coupling information between motors in the multi-motor drive system, calculate the electrical coupling coefficient based on the electrical coupling information, and evaluate the degree of electrical coupling influence between the multiple motors; A control coupling module is used to obtain the control coupling information between motors in a multi-motor drive system, calculate the control coupling coefficient based on the control coupling information, and evaluate the control coupling influence between the multiple motors; The identification and evaluation module constructs a single-point collaborative fault identification model based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, outputs a single-point collaborative fault identification index, and determines whether the abnormal mode identified by the existing fault detection method is a single-point motor fault or a system collaborative fault.

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