New energy vehicle drive motor safety management system and method based on intelligent control

Abstract

The present invention discloses a new energy vehicle drive motor safety management system and method based on intelligent control, and specifically relates to the technical field of drive motors. By obtaining mechanical transmission coupling information, a mechanical transmission coupling coefficient is calculated, so as to provide an important basis for evaluating the mechanical interaction between motors; by obtaining electrical coupling information between motors in a multi-motor drive system, an electrical coupling coefficient is calculated to further reveal the transmission and influence of electrical signals between motors, and help identify abnormalities in the electrical system; by obtaining control coupling information between motors in a multi-motor drive system, a control coupling coefficient is calculated to quantify the coupling degree of motor control signals, and to clarify the coordinated control behavior between motors. Each motor provides independent fault information, and the mechanical transmission coupling coefficient, electrical coupling coefficient and control coupling coefficient are integrated to construct a single-point coordinated fault identification model, which can effectively distinguish single-point motor faults from system coordinated faults.

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 popularity of electric vehicles, multi-motor drive systems, as one of its key technologies, have been widely used in new energy vehicles to improve driving performance, enhance system redundancy and improve energy efficiency. Multi-motor drive systems provide a smoother and more efficient driving experience by combining multiple motors to work together to optimize power output and achieve more precise control. However, as the complexity of the system increases, how to ensure the reliability and safety of multi-motor drive systems has become a major challenge facing the new energy vehicle field.

[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 the working state of multi-motor systems is usually highly coupled. The failure or abnormality of a single motor may affect the power distribution and coordinated work of the entire system, and system coordination problems (such as imbalance or energy distribution problems between motors) may also disguise as single motor failures. This makes the task of fault diagnosis more complicated, and the application effect of traditional fault detection methods in such systems may not be satisfactory. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the 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:

[0006] A new energy vehicle drive motor safety management method based on intelligent control includes the following steps:

[0007] 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;

[0008] 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;

[0009] 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;

[0010] 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.

[0011] 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 acquiring a mechanical transmission coupling coefficient, the interaction and mechanical coupling degree of each motor in the transmission system are measured;

[0012] The logic for obtaining the mechanical transmission coupling coefficient is as follows:

[0013] 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;

[0014] Calculate the motor speed coupling according to the actual motor speed , the expression is as follows

[0015] ,in Indicates The actual speed of the motor, , is a positive integer;

[0016] 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;

[0017] 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;

[0018] 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.

[0019] In a preferred embodiment, the electrical interaction and electrical coupling degree between the motors are analyzed by acquiring the electrical coupling information between the motors in the multi-motor drive system, and the electrical coupling coefficient is obtained to measure the electrical interaction and electrical coupling degree between the motors;

[0020] The logic for obtaining the electrical coupling coefficient is as follows:

[0021] Obtain electrical operating parameters of each motor, including but not limited to motor voltage and motor current;

[0022] 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;

[0023] An electrical coupling matrix is ​​constructed by using the electrical coupling degrees of the nth motor and the mth motor as matrix elements;

[0024] 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.

[0025] In a preferred embodiment, the control coupling degree between the motors in the multi-motor drive system is analyzed by the control coupling information between the motors, and the control coupling coefficient is obtained to measure the control coupling degree between the motors;

[0026] The logic for obtaining the control coupling coefficient is as follows:

[0027] 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 represents the standard deviation of the control signal of the vth motor;

[0028] 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;

[0029] 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

[0030] 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;

[0031] 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.

[0032] 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 the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, and Both are greater than 0.

[0033] In a preferred embodiment, the single-point collaborative fault identification index is compared with a 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:

[0034] 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;

[0035] 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.

[0036] In a preferred embodiment, a 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;

[0037] 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;

[0038] 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;

[0039] 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;

[0040] 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.

[0041] Technical effects and advantages of the present invention:

[0042] The present invention obtains mechanical transmission coupling information to calculate the mechanical transmission coupling coefficient, thereby providing an important basis for evaluating the mechanical interaction between motors; obtains electrical coupling information between motors in a multi-motor drive system to calculate the electrical coupling coefficient, thereby further revealing the transmission and influence of electrical signals between motors and helping to identify abnormalities in the electrical system; obtains control coupling information between motors in a multi-motor drive system to calculate the control coupling coefficient, thereby quantifying the coupling degree of motor control signals and clarifying the collaborative control behavior between motors; each motor provides independent fault information, and the mechanical transmission coupling coefficient, electrical coupling coefficient and control coupling coefficient are integrated to construct a single-point collaborative fault identification model, which can effectively distinguish between single-point motor faults and system collaborative faults. In a multi-motor system, especially when facing complex fault modes, a more accurate fault type judgment can be provided; by outputting a single-point collaborative fault identification index, the existing fault detection method can be helped to more accurately identify abnormal modes in the system, thereby avoiding misjudgment caused by single-point faults or hidden dangers caused by system collaborative faults. While improving the accuracy of fault diagnosis, the fault tolerance of the multi-motor drive system is also enhanced, thereby avoiding the paralysis of the entire system due to individual motor failures, and ensuring the redundancy and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0044] Figure 1 This is a flow chart of the method of Example 1 of the present invention;

[0045] Figure 2 This is a flow chart of the system of Example 2 of the present invention. DETAILED DESCRIPTION

[0046] 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.

[0047] Embodiment 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:

[0048] 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;

[0049] 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;

[0050] 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;

[0051] 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;

[0052] 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;

[0053] The mechanical transmission coupling coefficient is used to measure the degree of interaction and coupling between each motor in the transmission system, reflecting the power transmission efficiency, mechanical connection status and load sharing between 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 motors can be quantified. When the mechanical transmission coupling coefficient is high, that is, the coupling is good, the abnormality 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 or mechanical transmission abnormality between the motors, 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, 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.

[0054] Therefore, 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;

[0055] The logic for obtaining the mechanical transmission coupling coefficient is as follows:

[0056] 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;

[0057] 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, by installing a Hall sensor on the rotor of the motor to collect the actual speed of the motor, by installing a torque sensor on the motor shaft to collect the actual torque, and by installing a vibration sensor on the gears, couplings and other components of the motor to collect the vibration signals of key nodes;

[0058] 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;

[0059] 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;

[0060] 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;

[0061] 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 are greater than 0;

[0062] 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;

[0063] 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;

[0064] The electrical coupling coefficient is a key indicator for measuring the degree of electrical interaction and coordination between motors in a multi-motor drive system. In a multi-motor system, the 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 interdependence of electrical parameters such as current, voltage and load between motors, and can effectively capture the dynamic changes of electrical transmission between motors. When a system fails, the electrical coupling coefficient can help determine whether it is a single motor failure or a systemic failure caused by electrical coordination problems between multiple motors. If the electrical coupling coefficient is low, it means that the electrical dependence between the motors is weak, and the abnormality in the system is more likely to be caused by a single motor failure; on the contrary, if the electrical coupling coefficient is high, it means that the electrical connection between the motors is closer, and the failure of a single motor may cause a large change in the electrical behavior of the entire system, thereby causing a coordinated failure. Therefore, based on the analysis of the electrical coupling coefficient, it is possible to more accurately determine whether the abnormal mode is a single-point motor failure or a system coordinated failure. By quantifying the electrical coupling coefficient, the root cause of the failure can be better evaluated, and unnecessary maintenance or debugging caused by incorrect failure mode determination can be avoided, thereby improving the reliability and safety of the system. The beneficial effect of this determination process is not only to improve the accuracy of fault diagnosis, but also to quickly identify whether it is a local problem or a systemic problem when an electrical anomaly occurs in the system, so as to take more targeted diagnosis and treatment measures, reducing the risk of misdiagnosis and system downtime;

[0065] Therefore, by acquiring 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;

[0066] The logic for obtaining the electrical coupling coefficient is as follows:

[0067] Obtain electrical operating parameters of each motor, including but not limited to motor voltage and motor current;

[0068] 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;

[0069] An electrical coupling matrix is ​​constructed by using the electrical coupling degrees of the nth motor and the mth motor as matrix elements;

[0070] 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;

[0071] 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;

[0072] The control coupling coefficient is used to measure the coupling degree of the control strategies between motors. The control coupling coefficient reflects the degree of mutual influence between multiple motors through the control system. In a multi-motor drive system, each motor is usually coordinated through a shared control signal (such as reference voltage, speed control signal, etc.). The control coupling coefficient characterizes the control interaction between these motors. If the control coupling coefficient is high, it means that the control signals between the motors are strongly correlated and the system has a high synergy; if the control coupling coefficient is low, it means that the control signals between the motors are highly independent, and the motors in the system are relatively independent, which is more likely to be caused by a single-point motor failure. In the case of a single-point failure, the control signal of the faulty motor may have a large deviation from the signals of other motors, resulting in a decrease in the control coupling coefficient, while other motors maintain normal operation. The analysis method based on the control coupling coefficient can effectively determine whether the abnormal mode identified by the existing fault detection method is a single-point motor failure or a system coordination failure. In a multi-motor drive system, each motor usually works together through control signals to jointly optimize the system performance. However, when a fault occurs, the control coupling relationship between the motors will change, reflecting the nature of the fault. If a system coordination fault occurs, the control signals of multiple motors will show 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 to provide more accurate fault type judgments, avoiding confusion between systemic faults and single-point faults, and improving the accuracy and reliability of fault diagnosis.

[0073] 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 the control coupling coefficient is obtained to measure the control coupling degree between each motor;

[0074] The logic for obtaining the control coupling coefficient is as follows:

[0075] 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;

[0076] 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;

[0077] 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

[0078] 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;

[0079] 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 are greater than 0;

[0080] 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 both 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.

[0081] 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;

[0082] 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 All are greater than 0;

[0083] It should be noted that before constructing 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;

[0084] It can be seen from the above calculation expression 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;

[0085] 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:

[0086] If the single-point collaborative fault discrimination index is greater than the single-point collaborative fault discrimination index threshold, it indicates that the abnormal mode identified by the existing fault detection method is a single-point motor fault, and a single-point fault signal is generated;

[0087] If the single-point collaborative fault identification index is less than or equal to the single-point collaborative fault identification index threshold, it indicates that the abnormal mode identified by the existing fault detection method is a system collaborative fault, and a system collaborative fault signal is generated.

[0088] The present invention obtains mechanical transmission coupling information to calculate the mechanical transmission coupling coefficient, thereby providing an important basis for evaluating the mechanical interaction between motors; obtains electrical coupling information between motors in a multi-motor drive system to calculate the electrical coupling coefficient, thereby further revealing the transmission and influence of electrical signals between motors and helping to identify abnormalities in the electrical system; obtains control coupling information between motors in a multi-motor drive system to calculate the control coupling coefficient, thereby quantifying the coupling degree of motor control signals and clarifying the collaborative control behavior between motors; each motor provides independent fault information, and the mechanical transmission coupling coefficient, electrical coupling coefficient and control coupling coefficient are integrated to construct a single-point collaborative fault identification model, which can effectively distinguish between single-point motor faults and system collaborative faults. In a multi-motor system, especially when facing complex fault modes, a more accurate fault type judgment can be provided; by outputting a single-point collaborative fault identification index, the existing fault detection method can be helped to more accurately identify abnormal modes in the system, thereby avoiding misjudgment caused by single-point faults or hidden dangers caused by system collaborative faults. While improving the accuracy of fault diagnosis, the fault tolerance of the multi-motor drive system is also enhanced, thereby avoiding the paralysis of the entire system due to individual motor failures, and ensuring the redundancy and reliability of the system.

[0089] Embodiment 2: This embodiment 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;

[0090] 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;

[0091] 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;

[0092] 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;

[0093] 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.

[0094] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0095] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by 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 programs 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 site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access 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 hard disk.

[0096] 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.

[0097] Those skilled in the art can 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.

[0098] In several embodiments provided in this application, it should be understood that the disclosed systems and methods may be implemented in other ways.

[0099] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope 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; 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: Get the control signal of each motor and calculate the Pearson correlation coefficient pe of the control signal between motors u,v , the expression is as follows Where Cov(x(t) u ,x(t) v ) represents the covariance of the control signals of the u-th motor and the v-th motor, σ(x(t) u ) represents the standard deviation of the control signal of the u-th motor, σ(x(t) v ) represents the standard deviation of the control signal of the vth motor; The first control coupling degree Ko1 is calculated based on the Pearson correlation coefficient of the control signal between the motors. The expression is as follows: Where DZ represents the total number of motors; Calculate the cross spectral density S of the control signals between the motors u,v (f), the expression is as follows where x(t) u represents the control signal of the u-th motor, x * (t+τ) v represents the complex conjugate of the control signal of the vth motor after time-delay shift, τ represents the signal phase difference between motor u and motor v, j represents the imaginary unit, f represents the frequency, and [0, T] represents the integral time range of the time-delay τ; The second control coupling degree Ko2 is calculated according to the cross-spectral density of the control signals between the motors. The expression is as follows: Where DZ represents the total number of motors; The control coupling coefficient KZO is calculated, and the expression is as follows: KZO=b1*Ko1+b2*Ko2, wherein b1 and b2 represent the preset proportional coefficients of the first control coupling degree and the second control coupling degree respectively, and b1 and b2 are both greater than 0.

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: Acquire the actual speed, actual torque and vibration signals of key nodes of each motor, wherein the key nodes include gears and couplings; Calculate the motor speed coupling degree Cz according to the actual motor speed. The expression is as follows where zs i represents the actual speed of the i-th motor, i={1,2,...,I}, I is a positive integer; The motor torque coupling degree Cn is calculated according to the actual torque of the motor. The expression is as follows where nj i represents the actual torque of the i-th motor; The vibration coupling degree Co is calculated based on the vibration signal of the key nodes of the motor. The expression is as follows: Among them i represents the vibration signal of the i-th motor; Calculate the mechanical transmission coupling coefficient JXO, the expression is as follows JXO = a1*Cz+a2*Cn+a3*Co, where a1, a2, and a3 represent the preset proportional coefficients of motor speed coupling, motor torque coupling, and vibration coupling, respectively, and a1, a2, and a3 are all 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 the electrical operating parameters of each motor, including motor voltage and motor current; Calculate the electrical coupling cd between the nth motor and the mth motor n,m , the calculation expression is as follows Among them, Cov(V n ,V m ) represents the covariance of the voltages of the nth motor and the mth motor, Cov(L n ,L m ) represents the covariance of the current of the nth motor and the mth motor, σ(V n ) represents the standard deviation of the voltage of the nth motor, σ(V m ) represents the standard deviation of the voltage of the mth motor, σ(L n ) represents the standard deviation of the current of the nth motor, σ(L m ) 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; Calculate the electrical coupling coefficient DQO, the expression is as follows where cd n,m represents the electrical coupling degree between the nth motor and the mth motor, and ZS 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: A single-point collaborative fault identification model is constructed based on the mechanical transmission coupling coefficient, electrical coupling coefficient, and control coupling coefficient, and the single-point collaborative fault identification index DXZ is output. The formula based on the model is as follows Wherein w1, w2, and w3 represent preset proportional coefficients of the mechanical transmission coupling coefficient, the electrical coupling coefficient, and the control coupling coefficient, respectively, and w1, w2, and w3 are all greater than 0.

5. The method for safety management of driving motors of new energy vehicles based on intelligent control according to claim 4 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.

6. 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 5, 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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