New energy automobile driving motor control method and system based on predictive control

Abstract

The invention discloses a new energy automobile driving motor control method and system based on predictive control, and relates to the technical field of motor control. The system obtains a vibration correlation index Zxg, an axis state index Zst and a rotor deformation degree index Zbx through an advanced data acquisition and analysis technology; accurate monitoring and analysis of motor vibration, axis state and rotor deformation are realized; the method comprises the following steps of: acquiring a mechanical unbalance index Zsh through fitting after a machine deep learning technology and dimensionless processing, comparing and analyzing the mechanical unbalance index Zsh with a preset unbalance threshold H, acquiring a corresponding control instruction, and taking corresponding early warning and regulation measures according to the control instruction. The overall performance and energy efficiency of the new energy automobile are improved; and through a preliminary early warning mechanism and self-adaptive adjustment, potential problems can be recognized in the early stage, effective measures can be taken, and reliable guarantee is provided for safe operation of the motor and a whole vehicle system.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and in particular to a new energy vehicle drive motor control method and system based on predictive control. Background Art

[0002] With the rapid development of the new energy vehicle market, the drive motor, as the core component of new energy vehicles, undertakes the key function of converting electrical energy into mechanical energy; the performance and reliability of the drive motor directly affect the power output, energy efficiency and overall user experience of new energy vehicles; therefore, the importance of motor control technology in the field of new energy vehicles is becoming more and more prominent. Through precise motor control technology, not only can the efficiency and power performance of the drive motor be improved, but also its service life can be effectively extended and the occurrence rate of failures can be reduced.

[0003] In motor control, the mechanical imbalance of the drive motor is one of the important factors affecting the motor's performance and reliability. Mechanical imbalance is mainly manifested in rotor eccentricity, state deviation of the stator and rotor axes, and rotor deformation. These factors can cause abnormal vibration and noise in the motor during operation, and even lead to serious mechanical failures. Traditional motor control methods and systems often have the shortcomings of untimely detection, inaccurate analysis, and imperfect control measures when dealing with these problems, and the effect on improving the operating efficiency and service life of the drive motor is not obvious. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a new energy vehicle drive motor control method and system based on predictive control, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A new energy vehicle drive motor control system based on predictive control, including a first acquisition module, a correlation analysis module, a second acquisition module, a mechanical imbalance comprehensive analysis module and a motor control module;

[0006] The first acquisition module is used to detect the unused new energy vehicle drive motor in advance to determine the rotor coordinates in the motor and mark them as reference points. At the same time, the rotor relative offset data of the used new energy vehicle drive motor is detected to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set.

[0007] The correlation analysis module analyzes the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor based on the relative offset data and the motor vibration state data to generate a vibration correlation index Zxg, and compares and analyzes it with a preset correlation threshold L to determine whether to issue a preliminary warning instruction;

[0008] The second acquisition module is used to detect the axis state data information of the rotor and the stator during the operation of the motor through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain the rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor;

[0009] The mechanical imbalance comprehensive analysis module is used to perform feature extraction based on the axis state data information and the rotor deformation data information, obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and associate the axial spacing Lzj with the axial deflection angle Dpj to obtain the axis state index Zst, and obtain the rotor deformation index Zbx by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, fit and obtain the mechanical imbalance index Zsh;

[0010] The motor control module is used to compare and analyze the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module with a preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

[0011] Specifically, the first acquisition module includes a rotor offset data acquisition unit and a motor state information acquisition unit;

[0012] The rotor offset data acquisition unit is used to detect and record the relative offset data between the geometric center of the rotor in the used new energy vehicle drive motor and its rotation axis, wherein the relative offset data includes the rotor offset coordinates at each detection time point, and in combination with the reference point, the rotor eccentricity value Dpx at each detection time point is obtained using a displacement sensor.

[0013] Specifically, the motor state acquisition unit is used to use the displacement sensor to perform Fourier transform on the motor displacement signal in the motor vibration state data obtained when the new energy vehicle drive motor is in operation, and at the same time convert the operating time domain signal into the frequency domain, identify different frequency components and corresponding amplitudes in the frequency domain, and obtain the motor vibration frequency Pzd at each detection time point.

[0014] Specifically, the correlation analysis module includes a vibration correlation analysis unit and a determination unit;

[0015] The vibration correlation analysis unit is used to analyze the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor according to the relative offset data and the motor vibration state data, so as to generate a vibration correlation index Zxg. The vibration correlation index Zxg is obtained by the following formula:

[0016] ;

[0017] Where Dpx i Expressed as the rotor eccentricity value in the i-th acquisition period, Pzd i It is expressed as the motor vibration frequency in the i-th acquisition period, It is expressed as the mean value of the rotor eccentricity during the acquisition period, It is represented by the mean value of the motor vibration frequency within the acquisition period, i=1, 2, 3, ..., n, where n is the acquisition period;

[0018] The determination unit is used to pre-set a correlation threshold L, and compare and analyze the correlation threshold L with the vibration correlation index Zxg to determine whether the rotor offset has an impact on the motor operation state. The specific contents are as follows:

[0019] If the vibration correlation index Zxg> the correlation threshold L, it means that the deviation of the rotor during the current operation of the motor has an impact on the operation state of the motor, and a preliminary warning instruction is issued, and the rotor will be further analyzed at this time;

[0020] If the vibration correlation index Zxg is less than the correlation threshold L, it indicates that the rotor offset during the current motor operation has an impact on the motor operation state, and a preliminary warning instruction is issued, at which point the rotor will be further analyzed;

[0021] If the vibration correlation index Zxg=the correlation threshold L, it means that the offset of the rotor in the current motor operation process has no effect on the motor operation state, and no additional control instruction is issued at this time.

[0022] Specifically, the second acquisition module includes a deployment unit, an axis state acquisition unit and a deformation feature acquisition unit;

[0023] The deployment unit is used to install several groups of sensors in the drive motor, wherein the several groups of sensors include eddy current sensors, optical encoders, laser displacement sensors and capacitive sensors;

[0024] The axis state acquisition unit is used to detect the axis state data information of the rotor and the stator during the operation of the motor, and the axis state data information includes the axial spacing Lzj and the axial deviation angle Dpj;

[0025] The axial spacing Lzj is measured by installing an eddy current sensor inside the stator or on the motor housing. The eddy current sensor measures the gap between the rotor and the stator in a non-contact manner through the principle of electromagnetic induction. When the distance between the rotor and the sensor changes, the output signal of the sensor will also change accordingly. By real-time acquisition and analysis of these signals, the gap between the rotor and the stator center axis can be accurately measured in a non-contact manner.

[0026] The axial deviation angle Dpj is installed on the axis of the motor through an optical encoder. The light emitted by the encoder passes through the gap of the encoding disk, is reflected back to the sensor and generates an electrical pulse signal. The optical signal of the encoding disk on the rotating shaft is obtained to determine the angle of the rotor.

[0027] The deformation feature acquisition unit is used to obtain rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor. The rotor deformation data information includes the front main shaft deflection Rzr, the side main shaft deflection Rcr and the rotor winding warping Rqd.

[0028] The front spindle deflection Rzr and the side spindle deflection Rcr are installed at multiple positions of the stator through laser displacement sensors, facing different parts of the rotor. The sensor emits a laser beam and measures the echo time or phase change of the reflected light, thereby determining the measurement of the rotor shaft bending deformation;

[0029] The rotor winding warping degree Rqd is achieved by installing a capacitive sensor around the rotor winding to form a capacitive sensing area. When the winding warps, the change in distance between the winding and the capacitive sensor will cause a change in the capacitance value. By real-time acquisition and analysis of the changes in these capacitive signals, the warping degree of the winding can be accurately measured.

[0030] Specifically, the mechanical imbalance comprehensive analysis module includes an axis state analysis unit, a deformation feature analysis unit and a mechanical imbalance analysis unit;

[0031] The axis state analysis unit is used to analyze the axis state data information, and obtain the axis state index Zst after dimensionless processing. The axis state index Zst is obtained by the following formula:

[0032] ;

[0033] In the formula, Lzj represents the axial spacing, Dpj represents the axial deviation angle, a1 and a2 represent the preset proportional coefficients of the axial spacing Lzj and the axial deviation angle Dpj, respectively, wherein 0.25≤a1≤0.65, 0.21≤a2≤0.35, and 0.46≤a1+a2≤1.0, and C represents the first correction constant.

[0034] Specifically, the deformation feature analysis unit is used to analyze the rotor deformation data information, and obtain the rotor deformation index Zbx after dimensionless processing. The rotor deformation index Zbx is obtained by the following formula:

[0035] ;

[0036] In the formula, Rzr represents the front main shaft deflection, Rcr represents the side main shaft deflection, Rqd represents the rotor winding warping, b1 represents the preset proportional coefficient of the sum of the front main shaft deflection Rzr and the side main shaft deflection Rcr, b2 represents the preset proportional coefficient of the rotor winding warping Rqd, wherein 0.35≤b1≤0.63, 0.21≤b2≤0.37, and 0.56≤b1+b2≤1.0, and H represents the second correction constant.

[0037] Specifically, the mechanical imbalance analysis unit is used to utilize machine deep learning technology, and dimensionlessly process the vibration correlation index Zxg, the axis state index Zst, and the rotor deformation index Zbx, and obtain the mechanical imbalance index Zsh by fitting. The mechanical imbalance index Zsh is obtained by the following formula:

[0038] ;

[0039] In the formula, f1, f2 and f3 represent the preset proportional coefficients of the vibration correlation index Zxg, the axis state index Zst and the rotor deformation index Zbx respectively, among which, 0.25≤f1≤0.23, 0.21≤f2≤0.37, 0.23≤f3≤0.40, and 0.69≤f1+f2+f3≤1.0, and Y is represented as the third correction constant.

[0040] Specifically, the motor control module includes a comparison unit and a control unit;

[0041] The comparison unit is used to compare and analyze the mechanical imbalance index Zsh with the imbalance threshold H to obtain a control instruction. The specific analysis content of the control instruction is as follows:

[0042] If the mechanical imbalance index Zsh is less than the imbalance threshold H, it indicates that the motor operation state is currently normal, and no additional control instruction is issued;

[0043] If the mechanical imbalance index Zsh=the imbalance threshold H, it means that the motor operation state is abnormal at present, and a first control instruction is issued at this time;

[0044] If the mechanical imbalance index Zsh> the imbalance threshold H, it indicates that the motor operation state is abnormal at present, and a second control instruction is issued;

[0045] The control unit includes an early warning subunit and an adaptive adjustment subunit;

[0046] The warning subunit is used to receive the first control instruction and the second control instruction, and make corresponding warning prompts, including yellow warning and red warning, wherein when the first control instruction is issued, a yellow warning is generated, and when the second control instruction is issued, a red warning is generated;

[0047] The adaptive adjustment control subunit is used to make corresponding adaptive adjustment control measures according to different early warning prompts;

[0048] When a yellow warning is issued, the motor speed will be adjusted to achieve normal mechanical load and the current new energy vehicle drive motor operating data will be automatically recorded; maintenance personnel will be reminded of the motor's operating status through system notifications and regular inspections will be arranged; motor control parameters will be automatically adjusted according to the current imbalance situation;

[0049] When a red warning is issued, a preparation time will be set to notify the owner to park the vehicle in a safe area on the road within the specified preparation time to stop the operation of the motor and lock the motor to prohibit restarting in the fault state; an emergency maintenance notice will be issued through the system to notify relevant maintenance personnel to conduct on-site inspection and repairs; a detailed diagnostic procedure will be initiated to record and analyze all relevant operating data to determine the cause of the fault and formulate a maintenance plan, and an adaptive adjustment mechanism will be introduced into the control algorithm to adjust the motor operating parameters in real time, as well as automatically adjust the motor's balancing device.

[0050] A method for controlling a drive motor of a new energy vehicle based on predictive control comprises the following steps:

[0051] Step 1: First, pre-test the unused new energy vehicle drive motor to determine the rotor coordinates in the motor and mark them as reference points. At the same time, perform rotor relative offset data detection on the used new energy vehicle drive motor to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set.

[0052] Step 2: Based on the relative offset data and the motor vibration status data, the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor is analyzed to generate a vibration correlation index Zxg, and compared with the preset correlation threshold L to determine whether to issue a preliminary warning instruction;

[0053] Step 3: After receiving the preliminary warning instruction, the axis state data information of the rotor and the stator during the operation of the motor is detected by several sets of sensors, and the rotor deformation data information is obtained according to the thermal stress and mechanical stress on the rotor during the operation of the motor;

[0054] Step 4: Then, according to the axis state data information and the rotor deformation data information, feature extraction is performed to obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and the axial spacing Lzj is associated with the axial deflection angle Dpj to obtain the axis state index Zst, and the rotor deformation index Zbx is obtained by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, the mechanical imbalance index Zsh is obtained by fitting;

[0055] Step 5: Then, based on the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module, compare and analyze it with the preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

[0056] The present invention provides a new energy vehicle drive motor control method and system based on predictive control, which has the following beneficial effects:

[0057] (1) Through advanced data acquisition and analysis technology, the vibration correlation index Zxg, axis state index Zst and rotor deformation index Zbx are obtained, realizing accurate monitoring and analysis of motor vibration, axis state and rotor deformation; and after machine deep learning technology and dimensionless processing, the mechanical imbalance index Zsh is fitted and obtained, which is compared and analyzed with the preset imbalance threshold H to obtain the corresponding control instructions, and make corresponding early warning and control measures based on the control instructions. This design not only improves the stability and reliability of motor operation, but also effectively extends the service life of the motor, reduces the failure rate, and thus improves the overall performance and energy efficiency of new energy vehicles; through the preliminary early warning mechanism and adaptive adjustment, it can identify potential problems at an early stage and take effective measures, providing reliable guarantee for the safe operation of the motor and the whole vehicle system, and demonstrating the superiority of the new energy vehicle drive motor control system based on predictive control.

[0058] (2) At the same time, by real-time collection and analysis of motor vibration status data, combined with the correlation analysis of the rotor eccentricity value Dpx, a vibration correlation index Zxg is generated, and compared with the pre-set correlation threshold L to determine whether to issue a preliminary warning instruction. This can accurately evaluate the impact of motor vibration on performance and reliability. This accurate vibration warning system effectively prevents potential mechanical failures caused by vibration and improves the stability and reliability of motor operation.

[0059] (3) At the same time, the motor control module compares and analyzes the mechanical imbalance index Zsh with the preset imbalance threshold H, and issues early warnings and control instructions in a timely manner; when the mechanical imbalance problem is relatively minor, the system can automatically adjust the motor operating parameters to avoid further damage, and at the same time remind maintenance personnel to pay attention to the operating status of the motor; in the case of severe imbalance, the system can immediately shut down and issue an emergency maintenance notice, effectively preventing the expansion of mechanical failures and protecting the safety of the motor and the entire vehicle system. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a block diagram of a new energy vehicle drive motor control system based on predictive control according to the present invention;

[0061] Figure 2 The present invention is a schematic diagram of the steps of a new energy vehicle drive motor control method based on predictive control. DETAILED DESCRIPTION

[0062] 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.

[0063] Example 1, please refer to Figure 1 , the present invention provides a new energy vehicle drive motor control system based on predictive control, including a first acquisition module, a correlation analysis module, a second acquisition module, a mechanical imbalance comprehensive analysis module and a motor control module;

[0064] The first acquisition module is used to detect the unused new energy vehicle drive motor in advance to determine the rotor coordinates in the motor and mark them as reference points. At the same time, the rotor relative offset data of the used new energy vehicle drive motor is detected to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set.

[0065] The correlation analysis module analyzes the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor based on the relative offset data and the motor vibration state data to generate a vibration correlation index Zxg, and compares and analyzes it with a preset correlation threshold L to determine whether to issue a preliminary warning instruction;

[0066] The second acquisition module is used to detect the axis state data information of the rotor and the stator during the operation of the motor through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain the rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor;

[0067] The mechanical imbalance comprehensive analysis module is used to perform feature extraction based on the axis state data information and the rotor deformation data information, obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and associate the axial spacing Lzj with the axial deflection angle Dpj to obtain the axis state index Zst, and obtain the rotor deformation index Zbx by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, fit and obtain the mechanical imbalance index Zsh;

[0068] The motor control module is used to compare and analyze the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module with a preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

[0069] During the operation of this system, the first acquisition module pre-detects the rotor coordinates and constructs the reference point, monitors the motor vibration state in real time, and the correlation analysis module analyzes the impact of rotor eccentricity on vibration and generates a vibration correlation index. After receiving the preliminary warning instruction, the second acquisition module further detects the axis state and rotor deformation data. The mechanical imbalance comprehensive analysis module extracts feature data and fits the mechanical imbalance index Zsh through deep learning. The motor control module generates corresponding control instructions based on the comparison result between the index and the imbalance threshold H, thereby realizing accurate prediction and effective regulation of the motor imbalance state, and significantly improving the reliability and stability of the motor operation.

[0070] Example 2, please refer to Figure 1 , specifically: the first acquisition module includes a rotor offset data acquisition unit and a motor state information acquisition unit;

[0071] The rotor offset data acquisition unit is used to detect and record the relative offset data between the geometric center of the rotor in the used new energy vehicle drive motor and its rotation axis, wherein the relative offset data includes the rotor offset coordinates at each detection time point, and in combination with the reference point, the rotor eccentricity value Dpx at each detection time point is obtained using a displacement sensor.

[0072] Specifically, the motor state acquisition unit is used to use the displacement sensor to perform Fourier transform on the motor displacement signal in the motor vibration state data obtained when the new energy vehicle drive motor is in operation, and at the same time convert the operating time domain signal into the frequency domain, identify different frequency components and corresponding amplitudes in the frequency domain, and obtain the motor vibration frequency Pzd at each detection time point.

[0073] In this embodiment, the relative offset data and vibration state of the rotor in the used new energy vehicle drive motor are detected and recorded in detail through the rotor offset data acquisition unit and the motor state information acquisition unit in the first acquisition module; the rotor offset data acquisition unit uses a displacement sensor to detect the rotor offset coordinates at each time point, and obtains the rotor eccentricity value Dpx in combination with the reference point; the motor state information acquisition unit uses the displacement sensor to perform Fourier transform on the vibration data of the motor under the running state, and converts the time domain signal into a frequency domain signal, thereby identifying different frequency components and their amplitudes, and obtaining the motor vibration frequency Pzd at each time point; this system design not only improves the accuracy and real-time performance of data acquisition, but also enhances the ability to identify the vibration characteristics of the motor through frequency domain analysis, and provides reliable data support for the subsequent vibration correlation index Zxg analysis and mechanical imbalance index Zsh.

[0074] Example 3, please refer to Figure 1 , specifically: the correlation analysis module includes a vibration correlation analysis unit and a determination unit;

[0075] The vibration correlation analysis unit is used to analyze the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor according to the relative offset data and the motor vibration state data, so as to generate a vibration correlation index Zxg. The vibration correlation index Zxg is obtained by the following formula:

[0076] ;

[0077] Where Dpx i Expressed as the rotor eccentricity value in the i-th acquisition period, Pzd i It is expressed as the motor vibration frequency in the i-th acquisition period, It is expressed as the mean value of the rotor eccentricity during the acquisition period, It is represented by the mean value of the motor vibration frequency within the acquisition period, i=1, 2, 3, ..., n, where n is the acquisition period;

[0078] The determination unit is used to pre-set a correlation threshold L, and compare and analyze the correlation threshold L with the vibration correlation index Zxg to determine whether the rotor offset has an impact on the motor operation state. The specific contents are as follows:

[0079] If the vibration correlation index Zxg> the correlation threshold L, it means that the deviation of the rotor during the current operation of the motor has an impact on the operation state of the motor, and a preliminary warning instruction is issued, and the rotor will be further analyzed at this time;

[0080] If the vibration correlation index Zxg is less than the correlation threshold L, it indicates that the rotor offset during the current motor operation has an impact on the motor operation state, and a preliminary warning instruction is issued, at which point the rotor will be further analyzed;

[0081] If the vibration correlation index Zxg=the correlation threshold L, it means that the offset of the rotor in the current motor operation process has no effect on the motor operation state, and no additional control instruction is issued at this time.

[0082] In this embodiment, based on the relative offset data and the motor vibration status data, the influence of the rotor eccentricity value Dpx on the motor vibration is accurately analyzed to generate a vibration correlation index Zxg; the vibration correlation index Zxg is calculated by a specific formula, taking into account the mean and fluctuation of the rotor eccentricity value and the motor vibration frequency during the acquisition period; the determination unit compares and analyzes the generated vibration correlation index Zxg with the pre-set correlation threshold L to determine whether the rotor offset has an impact on the motor operating state; when Zxg is greater than or less than the threshold L, the system issues a preliminary early warning instruction, prompting further analysis of the rotor; if Zxg is equal to the threshold L, it indicates that the rotor offset has not yet affected the motor operating state, and no additional control instructions are issued; through this system design, it is possible to effectively warn and determine the impact of the rotor offset on the motor operating state in advance.

[0083] Example 4, please refer to Figure 1 ,Specifically: the second acquisition module includes a deployment unit, an axis state acquisition unit and a deformation feature acquisition unit;

[0084] The deployment unit is used to install several groups of sensors in the drive motor, wherein the several groups of sensors include eddy current sensors, optical encoders, laser displacement sensors and capacitive sensors;

[0085] The axis state acquisition unit is used to detect the axis state data information of the rotor and the stator during the operation of the motor, and the axis state data information includes the axial spacing Lzj and the axial deviation angle Dpj;

[0086] The axial spacing Lzj is measured by installing an eddy current sensor inside the stator or on the motor housing. The eddy current sensor measures the gap between the rotor and the stator in a non-contact manner through the principle of electromagnetic induction. When the distance between the rotor and the sensor changes, the output signal of the sensor will also change accordingly. By real-time acquisition and analysis of these signals, the gap between the rotor and the stator center axis can be accurately measured in a non-contact manner.

[0087] The axial deviation angle Dpj is installed on the axis of the motor through an optical encoder. The light emitted by the encoder passes through the gap of the encoding disk, is reflected back to the sensor and generates an electrical pulse signal. The optical signal of the encoding disk on the rotating shaft is obtained to determine the angle of the rotor.

[0088] The deformation feature acquisition unit is used to obtain rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor. The rotor deformation data information includes the front main shaft deflection Rzr, the side main shaft deflection Rcr and the rotor winding warping Rqd.

[0089] The front spindle deflection Rzr and the side spindle deflection Rcr are installed at multiple positions of the stator through laser displacement sensors, facing different parts of the rotor. The sensor emits a laser beam and measures the echo time or phase change of the reflected light, thereby determining the measurement of the rotor shaft bending deformation;

[0090] The rotor winding warping degree Rqd is achieved by installing a capacitive sensor around the rotor winding to form a capacitive sensing area. When the winding warps, the change in distance between the winding and the capacitive sensor will cause a change in the capacitance value. By real-time acquisition and analysis of the changes in these capacitive signals, the warping degree of the winding can be accurately measured.

[0091] In this embodiment, accurate status monitoring of the rotor and stator in the new energy vehicle drive motor is achieved through the deployment unit, axis state acquisition unit and deformation feature acquisition unit included in the second acquisition module; the deployment unit installs eddy current sensors, optical encoders, laser displacement sensors and capacitive sensors in the motor; the axis state acquisition unit measures the axial spacing Lzj in a non-contact manner through the eddy current sensor, and obtains the axial deviation angle Dpj using the optical encoder; the deformation feature acquisition unit uses a laser displacement sensor to detect the front spindle deflection Rzr and the side spindle deflection Rcr, and measures the rotor winding warpage Rqd through a capacitive sensor; this system design can collect various key parameters in the motor operation process with high precision and in real time, comprehensively grasp the mechanical status of the rotor and stator in the motor, and identify potential problems in advance, thereby significantly improving the reliability and stability of the motor operation and extending the service life of the motor.

[0092] Example 5, please refer to Figure 1 , specifically: the mechanical imbalance comprehensive analysis module includes an axis state analysis unit, a deformation feature analysis unit and a mechanical imbalance analysis unit;

[0093] The axis state analysis unit is used to analyze the axis state data information, and obtain the axis state index Zst after dimensionless processing. The axis state index Zst is obtained by the following formula:

[0094] ;

[0095] In the formula, Lzj represents the axial spacing, Dpj represents the axial deviation angle, a1 and a2 represent the preset proportional coefficients of the axial spacing Lzj and the axial deviation angle Dpj, respectively, wherein 0.25≤a1≤0.65, 0.21≤a2≤0.35, and 0.46≤a1+a2≤1.0, and C represents the first correction constant.

[0096] Specifically, the deformation feature analysis unit is used to analyze the rotor deformation data information, and obtain the rotor deformation index Zbx after dimensionless processing. The rotor deformation index Zbx is obtained by the following formula:

[0097] ;

[0098] In the formula, Rzr represents the front main shaft deflection, Rcr represents the side main shaft deflection, Rqd represents the rotor winding warping, b1 represents the preset proportional coefficient of the sum of the front main shaft deflection Rzr and the side main shaft deflection Rcr, b2 represents the preset proportional coefficient of the rotor winding warping Rqd, wherein 0.35≤b1≤0.63, 0.21≤b2≤0.37, and 0.56≤b1+b2≤1.0, and H represents the second correction constant.

[0099] Specifically, the mechanical imbalance analysis unit is used to utilize machine deep learning technology, and dimensionlessly process the vibration correlation index Zxg, the axis state index Zst, and the rotor deformation index Zbx, and obtain the mechanical imbalance index Zsh by fitting. The mechanical imbalance index Zsh is obtained by the following formula:

[0100] ;

[0101] In the formula, f1, f2 and f3 represent the preset proportional coefficients of the vibration correlation index Zxg, the axis state index Zst and the rotor deformation index Zbx respectively, among which, 0.25≤f1≤0.23, 0.21≤f2≤0.37, 0.23≤f3≤0.40, and 0.69≤f1+f2+f3≤1.0, and Y is represented as the third correction constant.

[0102] In this embodiment, the mechanical imbalance state of the new energy vehicle drive motor is accurately evaluated through the axis state analysis unit, deformation feature analysis unit and mechanical imbalance analysis unit included in the mechanical imbalance comprehensive analysis module; the axis state analysis unit performs dimensionless processing on the axial spacing Lzj and the axial deviation angle Dpj to calculate the axis state index Zst; the deformation feature analysis unit analyzes the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warping Rqd to obtain the rotor deformation index Zbx; the mechanical imbalance analysis unit combines machine deep learning technology, uses the vibration correlation index Zxg, the axis state index Zst and the rotor deformation index Zbx, and performs dimensionless processing to fit the mechanical imbalance index Zsh; this system design can efficiently and accurately identify and predict the mechanical imbalance state of the motor through sophisticated data analysis and deep learning technology, thereby providing timely warning and control measures, and improving the reliability and safety of the motor operation.

[0103] Example 6, please refer to Figure 1 ,Specifically: the motor control module includes a comparison unit and a control unit;

[0104] The comparison unit is used to compare and analyze the mechanical imbalance index Zsh with the imbalance threshold H to obtain a control instruction. The specific analysis content of the control instruction is as follows:

[0105] If the mechanical imbalance index Zsh is less than the imbalance threshold H, it indicates that the motor operation state is currently normal, and no additional control instruction is issued;

[0106] If the mechanical imbalance index Zsh=the imbalance threshold H, it means that the motor operation state is abnormal at present, and a first control instruction is issued at this time;

[0107] If the mechanical imbalance index Zsh> the imbalance threshold H, it indicates that the motor operation state is abnormal at present, and a second control instruction is issued;

[0108] The control unit includes an early warning subunit and an adaptive adjustment subunit;

[0109] The warning subunit is used to receive the first control instruction and the second control instruction, and make corresponding warning prompts, including yellow warning and red warning, wherein when the first control instruction is issued, a yellow warning is generated, and when the second control instruction is issued, a red warning is generated;

[0110] The adaptive adjustment control subunit is used to make corresponding adaptive adjustment control measures according to different early warning prompts;

[0111] When a yellow warning is issued, the motor speed will be adjusted to achieve normal mechanical load and the current new energy vehicle drive motor operating data will be automatically recorded; maintenance personnel will be reminded of the motor's operating status through system notifications and regular inspections will be arranged; motor control parameters will be automatically adjusted according to the current imbalance situation;

[0112] When a red warning is issued, a preparation time will be set to notify the owner to park the vehicle in a safe area on the road within the specified preparation time to stop the operation of the motor and lock the motor to prohibit restarting in the fault state; an emergency maintenance notice will be issued through the system to notify relevant maintenance personnel to conduct on-site inspection and repairs; a detailed diagnostic procedure will be initiated to record and analyze all relevant operating data to determine the cause of the fault and formulate a maintenance plan, and an adaptive adjustment mechanism will be introduced into the control algorithm to adjust the motor operating parameters in real time, as well as automatically adjust the motor's balancing device.

[0113] In this embodiment, through the comparison unit and the control unit in the motor control module, the mechanical imbalance state of the new energy vehicle drive motor can be accurately evaluated, and corresponding early warning and control measures can be made; the comparison unit compares and analyzes the mechanical imbalance index Zsh with the imbalance threshold H to generate specific control instructions; the control unit includes an early warning subunit and an adaptive adjustment subunit, and the early warning subunit issues a yellow warning or a red warning according to the control instruction, prompting maintenance personnel to pay attention to the motor operation status; the adaptive adjustment subunit automatically adjusts the motor speed during the yellow warning, records the operation data, and arranges regular inspections; sets the preparation time during the red warning, issues an emergency maintenance notice, and starts a detailed diagnostic procedure to adjust the motor operation parameters and the balancing device in real time; this system design can identify the motor imbalance state in advance, provide timely early warning and precise control, improve the safety, stability and maintenance efficiency of the motor operation, avoid further deterioration of the fault, and demonstrate the superiority of the new energy vehicle drive motor control system based on predictive control.

[0114] Example 7, please refer to Figure 1 and Figure 2 Specifically: A new energy vehicle drive motor control method based on predictive control includes the following steps:

[0115] Step 1: First, pre-test the unused new energy vehicle drive motor to determine the rotor coordinates in the motor and mark them as reference points. At the same time, perform rotor relative offset data detection on the used new energy vehicle drive motor to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set.

[0116] Step 2: Based on the relative offset data and the motor vibration status data, the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor is analyzed to generate a vibration correlation index Zxg, and compared with the preset correlation threshold L to determine whether to issue a preliminary warning instruction;

[0117] Step 3: After receiving the preliminary warning instruction, the axis state data information of the rotor and the stator during the operation of the motor is detected by several sets of sensors, and the rotor deformation data information is obtained according to the thermal stress and mechanical stress on the rotor during the operation of the motor;

[0118] Step 4: Then, according to the axis state data information and the rotor deformation data information, feature extraction is performed to obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and the axial spacing Lzj is associated with the axial deflection angle Dpj to obtain the axis state index Zst, and the rotor deformation index Zbx is obtained by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, the mechanical imbalance index Zsh is obtained by fitting;

[0119] Step 5: Then, based on the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module, compare and analyze it with the preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

[0120] In this embodiment, the method can establish an accurate reference model by predetermining the reference point and collecting the rotor eccentricity value and the motor vibration status data in real time, providing basic data for subsequent analysis. Real-time detection and data set construction can ensure that abnormalities are discovered in time during operation to avoid potential mechanical failures. By analyzing the influence of the eccentricity value on the vibration, the influence of the rotor offset on the motor operation state can be quantified, and the vibration correlation index Zxg can be generated, which is then compared and analyzed with the threshold value L to promptly determine whether an early warning is needed. Problems can be discovered at an early stage, and measures can be taken in advance to prevent the expansion of faults. Using a variety of sensors to perform detailed detection of the motor axis state and deformation data can obtain accurate axial spacing, axial deflection angle and deformation characteristics, which can A more comprehensive understanding of the motor's operating status and potential problems can provide more reliable basic data for subsequent analysis; detailed feature extraction and data processing can generate accurate axis state index Zst and rotor deformation index Zbx, and use machine deep learning technology and dimensionless processing methods to fit and obtain the mechanical imbalance index Zsh, which improves the accuracy and reliability of data analysis, thereby enabling a more accurate assessment of the motor's mechanical imbalance status; through comparative analysis of the mechanical imbalance index Zsh and the imbalance threshold H, the motor's operating status can be accurately judged and corresponding control instructions can be generated; early warning and control measures implemented according to the control instructions can effectively prevent damage to the motor caused by mechanical imbalance, ensure the safe operation of the motor, and extend the service life of the equipment.

[0121] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A new energy vehicle drive motor control system based on predictive control, characterized in that: It includes a first acquisition module, a correlation analysis module, a second acquisition module, a mechanical imbalance comprehensive analysis module and a motor control module; The first acquisition module is used to detect the unused new energy vehicle drive motor in advance to determine the rotor coordinates in the motor and mark them as reference points. At the same time, the rotor relative offset data of the used new energy vehicle drive motor is detected to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set. The correlation analysis module analyzes the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor based on the relative offset data and the motor vibration state data to generate a vibration correlation index Zxg, and compares and analyzes it with a preset correlation threshold L to determine whether to issue a preliminary warning instruction; The second acquisition module is used to detect the axis state data information of the rotor and the stator during the operation of the motor through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain the rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor; The mechanical imbalance comprehensive analysis module is used to perform feature extraction based on the axis state data information and the rotor deformation data information, obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and associate the axial spacing Lzj with the axial deflection angle Dpj to obtain the axis state index Zst, and obtain the rotor deformation index Zbx by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, fit and obtain the mechanical imbalance index Zsh; The motor control module is used to compare and analyze the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module with a preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

2. A new energy vehicle drive motor control system based on predictive control according to claim 1, characterized in that: The first acquisition module includes a rotor offset data acquisition unit and a motor state information acquisition unit; The rotor offset data acquisition unit is used to detect and record the relative offset data between the geometric center of the rotor in the used new energy vehicle drive motor and its rotation axis, wherein the relative offset data includes the rotor offset coordinates at each detection time point, and in combination with the reference point, the rotor eccentricity value Dpx at each detection time point is obtained using a displacement sensor.

3. A new energy vehicle drive motor control system based on predictive control according to claim 2, characterized in that: The motor state acquisition unit is used to use the displacement sensor to perform Fourier transform on the motor displacement signal in the motor vibration state data acquired when the new energy vehicle drive motor is in operation, and at the same time convert the operating time domain signal into the frequency domain, identify different frequency components and corresponding amplitudes in the frequency domain, and obtain the motor vibration frequency Pzd at each detection time point.

4. The new energy vehicle drive motor control system based on predictive control according to claim 1 is characterized in that: The correlation analysis module includes a vibration correlation analysis unit and a determination unit; The vibration correlation analysis unit is used to analyze the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor according to the relative offset data and the motor vibration state data, so as to generate a vibration correlation index Zxg. The vibration correlation index Zxg is obtained by the following formula: ； Where Dpx i Expressed as the rotor eccentricity value in the i-th acquisition period, Pzd i It is expressed as the motor vibration frequency in the i-th acquisition period, It is expressed as the mean value of the rotor eccentricity during the acquisition period, It is represented by the mean value of the motor vibration frequency within the acquisition period, i=1, 2, 3, ..., n, where n is the acquisition period; The determination unit is used to pre-set a correlation threshold L, and compare and analyze the correlation threshold L with the vibration correlation index Zxg to determine whether the rotor offset has an impact on the motor operation state. The specific contents are as follows: If the vibration correlation index Zxg> the correlation threshold L, it means that the deviation of the rotor during the current operation of the motor has an impact on the operation state of the motor, and a preliminary warning instruction is issued, and the rotor will be further analyzed at this time; If the vibration correlation index Zxg is less than the correlation threshold L, it indicates that the rotor offset during the current motor operation has an impact on the motor operation state, and a preliminary warning instruction is issued, at which point the rotor will be further analyzed; If the vibration correlation index Zxg=the correlation threshold L, it means that the offset of the rotor in the current motor operation process has no effect on the motor operation state, and no additional control instruction is issued at this time.

5. The new energy vehicle drive motor control system based on predictive control according to claim 1 is characterized in that: The second acquisition module includes a deployment unit, an axis state acquisition unit and a deformation feature acquisition unit; The deployment unit is used to install several groups of sensors in the drive motor, wherein the several groups of sensors include eddy current sensors, optical encoders, laser displacement sensors and capacitive sensors; The axis state acquisition unit is used to detect the axis state data information of the rotor and the stator during the operation of the motor, and the axis state data information includes the axial spacing Lzj and the axial deviation angle Dpj; The deformation feature acquisition unit is used to obtain rotor deformation data information according to the thermal stress and mechanical stress to which the rotor is subjected during the operation of the motor. The rotor deformation data information includes the front main shaft deflection Rzr, the side main shaft deflection Rcr and the rotor winding warping Rqd.

6. A new energy vehicle drive motor control system based on predictive control according to claim 1, characterized in that: The mechanical imbalance comprehensive analysis module includes an axis state analysis unit, a deformation feature analysis unit and a mechanical imbalance analysis unit; The axis state analysis unit is used to analyze the axis state data information, and obtain the axis state index Zst after dimensionless processing. The axis state index Zst is obtained by the following formula: ； In the formula, Lzj represents the axial spacing, Dpj represents the axial deviation angle, a1 and a2 represent the preset proportional coefficients of the axial spacing Lzj and the axial deviation angle Dpj respectively, and C represents the first correction constant.

7. A new energy vehicle drive motor control system based on predictive control according to claim 6, characterized in that: The deformation feature analysis unit is used to analyze the rotor deformation data information, and obtain the rotor deformation index Zbx after dimensionless processing. The rotor deformation index Zbx is obtained by the following formula: ； In the formula, Rzr represents the front main shaft deflection, Rcr represents the side main shaft deflection, Rqd represents the rotor winding warping, b1 represents the preset proportional coefficient of the sum of the front main shaft deflection Rzr and the side main shaft deflection Rcr, b2 represents the preset proportional coefficient of the rotor winding warping Rqd, and H represents the second correction constant.

8. The new energy vehicle drive motor control system based on predictive control according to claim 6 is characterized in that: The mechanical imbalance analysis unit is used to utilize machine deep learning technology, and dimensionlessly process the vibration correlation index Zxg, the axis state index Zst, and the rotor deformation index Zbx, and obtain the mechanical imbalance index Zsh by fitting. The mechanical imbalance index Zsh is obtained by the following formula: ； Wherein, f1, f2 and f3 represent the preset proportional coefficients of the vibration correlation index Zxg, the axis state index Zst and the rotor deformation index Zbx respectively, and Y represents the third correction constant.

9. The new energy vehicle drive motor control system based on predictive control according to claim 1 is characterized in that: The motor control module includes a comparison unit and a control unit; The comparison unit is used to compare and analyze the mechanical imbalance index Zsh with the imbalance threshold H to obtain a control instruction. The specific analysis content of the control instruction is as follows: If the mechanical imbalance index Zsh is less than the imbalance threshold H, it indicates that the motor operation state is currently normal, and no additional control instruction is issued; If the mechanical imbalance index Zsh=the imbalance threshold H, it means that the motor operation state is abnormal at present, and a first control instruction is issued at this time; If the mechanical imbalance index Zsh> the imbalance threshold H, it indicates that the motor operation state is abnormal at present, and a second control instruction is issued; The control unit includes an early warning subunit and an adaptive adjustment subunit; The warning subunit is used to receive the first control instruction and the second control instruction, and make corresponding warning prompts, including yellow warning and red warning, wherein when the first control instruction is issued, a yellow warning is generated, and when the second control instruction is issued, a red warning is generated; The adaptive adjustment control subunit is used to make corresponding adaptive adjustment control measures according to different early warning prompts; When a yellow warning is issued, the motor speed will be adjusted to achieve normal mechanical load and the current new energy vehicle drive motor operating data will be automatically recorded; maintenance personnel will be reminded of the motor's operating status through system notifications and regular inspections will be arranged; motor control parameters will be automatically adjusted according to the current imbalance situation; When a red warning is issued, a preparation time will be set to notify the owner to park the vehicle in a safe area on the road within the specified preparation time to stop the operation of the motor and lock the motor to prohibit restarting in the fault state; an emergency maintenance notice will be issued through the system to notify relevant maintenance personnel to conduct on-site inspection and repairs; a detailed diagnostic procedure will be initiated to record and analyze all relevant operating data to determine the cause of the fault and formulate a maintenance plan, and an adaptive adjustment mechanism will be introduced into the control algorithm to adjust the motor operating parameters in real time, as well as automatically adjust the motor's balancing device.

10. A method for controlling a new energy vehicle drive motor based on predictive control, used to implement a new energy vehicle drive motor control system based on predictive control as described in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: First, pre-test the unused new energy vehicle drive motor to determine the rotor coordinates in the motor and mark them as reference points. At the same time, perform rotor relative offset data detection on the used new energy vehicle drive motor to collect the rotor eccentricity value Dpx. During the operation of the new energy motor, the motor vibration state data is detected in real time to construct a motor vibration state data set. Step 2: Based on the relative offset data and the motor vibration status data, the influence of the rotor eccentricity value Dpx on the vibration of the new energy motor is analyzed to generate a vibration correlation index Zxg, and compared with the preset correlation threshold L to determine whether to issue a preliminary warning instruction; Step 3: After receiving the preliminary warning instruction, the axis state data information of the rotor and the stator during the operation of the motor is detected by several sets of sensors, and the rotor deformation data information is obtained according to the thermal stress and mechanical stress on the rotor during the operation of the motor; Step 4: Then, according to the axis state data information and the rotor deformation data information, feature extraction is performed to obtain the axial spacing Lzj, the axial deflection angle Dpj, the front spindle deflection Rzr, the side spindle deflection Rcr and the rotor winding warpage Rqd, and the axial spacing Lzj is associated with the axial deflection angle Dpj to obtain the axis state index Zst, and the rotor deformation index Zbx is obtained by associating the front spindle deflection Rzr and the side spindle deflection Rcr with the rotor winding warpage Rqd, and after machine deep learning technology and dimensionless processing, the mechanical imbalance index Zsh is obtained by fitting; Step 5: Then, based on the mechanical imbalance index Zsh obtained in the mechanical imbalance comprehensive analysis module, compare and analyze it with the preset imbalance threshold H, obtain corresponding control instructions, and make corresponding early warning and control measures according to the control instructions.

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