A temperature and vibration amplitude monitoring and analysis control system for a permanent magnet motor

Abstract

The application relates to the technical field of permanent magnet motors, and particularly discloses a temperature and vibration amplitude monitoring, analyzing and controlling system of a permanent magnet motor, which comprises the following modules: an initial module: grouping flow velocity nodes and vibration force nodes, keeping the load of the permanent magnet motor to reach a load node i, and acquiring the temperature and vibration amplitude of the permanent magnet motor in real time; a model establishing module: adjusting the flow velocity of a cooling medium and the vibration force applied to the permanent magnet motor to meet grouping f1, and acquiring the temperature and vibration amplitude of the permanent magnet motor in real time; after the temperature and vibration amplitude corresponding to all groupings are acquired, a state space model is constructed; an adjusting module: acquiring a target model, outputting a state vector Z1 based on the target model, and adjusting the temperature and vibration amplitude of the permanent magnet motor based on the state vector Z1. The application can realize synchronous prediction and optimization control of the temperature and vibration amplitude of the permanent magnet motor.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of permanent magnet motor, and particularly relates to a temperature and vibration amplitude monitoring and analysis control system of a permanent magnet motor. BACKGROUND

[0002] The permanent magnet motor is a motor using a permanent magnet to establish an excitation magnetic field, and has the characteristics of high efficiency, high power density and compact structure. The core thereof is composed of a stator, a rotor and a permanent magnet, and the permanent magnet replaces the traditional electric excitation winding, and no additional electric energy is needed to generate a magnetic field, thereby significantly reducing energy consumption.

[0003] In the operation of the permanent magnet motor, temperature and vibration amplitude are strongly coupled and interfered, and existing control methods are mostly to separately adjust a certain parameter, which is easy to cause a chain problem. High temperature can cause demagnetization of the permanent magnet and aging of the insulation, and excessive vibration amplitude can aggravate the wear of components and increase energy consumption, and the two influence each other to form a vicious cycle. The traditional control lacks quantitative processing of the coupling relationship between the two, and when adjusting, it is easy to lose one thing while gaining another, for example, the temperature reduction operation can increase vibration due to thermal deformation of components, and the vibration suppression measure can cause temperature rise due to increased friction, ultimately causing a decrease in equipment efficiency and frequent failures, and it is difficult to balance the operation stability and service life. SUMMARY

[0004] The present application relates to the technical field of permanent magnet motor, and particularly relates to a temperature and vibration amplitude monitoring and analysis control system of a permanent magnet motor.

[0005] The present application relates to the technical field of permanent magnet motor, and particularly relates to a temperature and vibration amplitude monitoring and analysis control system of a permanent magnet motor.

[0006] A temperature and vibration amplitude monitoring and analysis control system of a permanent magnet motor, comprising:

[0007] An initial module: a plurality of load nodes, flow rate nodes and vibration force nodes are set, the flow rate nodes and the vibration force nodes are grouped, the load of the permanent magnet motor reaches the load node i, and the temperature and the vibration amplitude of the permanent magnet motor are obtained in real time;

[0008] A model establishing module: when the temperature and the vibration amplitude reach a steady state, the flow rate of the cooling medium and the vibration force applied to the permanent magnet motor satisfy the grouping f1, the temperature and the vibration amplitude of the permanent magnet motor are obtained in real time, and the temperature and the vibration amplitude reach a steady state again;

[0009] The flow rate of the cooling medium and the vibration force applied to the permanent magnet motor satisfy the remaining groupings, and the above steps are repeated; after obtaining the temperature and the vibration amplitude corresponding to all groupings, a state space model when the load reaches the load node i is constructed based on a subspace identification method;

[0010] The adjusting module is configured to adjust the temperature and the vibration amplitude of the permanent magnet motor to reach a preset normal temperature N1ys and a preset normal vibration amplitude N2ys, respectively, based on the state space model.

[0011] As a further aspect of the present application, the grouping of the flow rate nodes and the vibration force nodes comprises:

[0012] A plurality of load nodes, flow rate nodes and vibration force nodes are arranged in a preset load range, a preset cooling medium flow rate range and a preset vibration force range, respectively.

[0013] One flow rate node and one vibration force node are included in one group, and the flow rate nodes and / or the vibration force nodes in different groups are different.

[0014] As a further aspect of the present application, when the variance of the continuous n temperatures is less than a preset temperature variance threshold, it is determined that the temperature reaches a steady state.

[0015] When the variance of the continuous n vibration amplitudes is less than a preset vibration amplitude variance threshold, it is determined that the vibration amplitude reaches a steady state.

[0016] As a further aspect of the present application, if the variance of the continuous ηn vibration amplitudes or temperatures does not reach a steady state, an error message is sent for prompting, and η is a preset multiple and η≥5.

[0017] As a further aspect of the present application, adjusting the temperature and the vibration amplitude of the permanent magnet motor to reach a preset normal temperature N1ys and a preset normal vibration amplitude N2ys comprises:

[0018] The state space model corresponding to the current load D1 of the permanent magnet motor is taken as a target model, the current load D1, the temperature D2, the vibration amplitude D3, the flow rate D4 of the cooling medium and the vibration force D5 of the permanent magnet motor are substituted into the target model, and a state vector Z1 is output. The temperature and the vibration amplitude of the permanent magnet motor are adjusted to reach a preset normal temperature N1ys and a preset normal vibration amplitude N2ys, respectively, based on the state vector Z1.

[0019] As a further aspect of the present application, adjusting the temperature and the vibration amplitude of the permanent magnet motor to reach a preset normal temperature N1ys and a preset normal vibration amplitude N2ys further comprises:

[0020] The target vector is obtained by correcting the state vector Z1 through a state observer.

[0021] The temperature N1 and the vibration amplitude N2 in the target vector are extracted, and a temperature difference N1'=N1-N1ys and a vibration amplitude difference N2'=N2-N2ys are calculated.

[0022] Based on the MPC algorithm and the temperature difference and the vibration amplitude difference, the temperature and the vibration amplitude are guaranteed to reach the preset normal temperature N1ys and the normal vibration amplitude N2ys respectively.

[0023] As a further scheme of the application: the normal temperature N1ys and the normal vibration amplitude N2ys change based on the change of the load.

[0024] The beneficial effects of the application: compared with the prior art:

[0025] 1. The application guarantees the stability and effectiveness of the collected data by setting the test data collection module, orderly adjusting the cooling medium flow rate and the vibration force under multiple load nodes, and combining the steady state determination condition to systematically observe the dynamic changes of the temperature and the vibration amplitude.

[0026] 2. The application constructs a multiple-input multiple-output state space model based on the subspace identification method, and introduces a pseudo-random binary excitation and a closed-loop identification method, so that the temperature and the vibration amplitude obtain high-quality model parameters under the premise of keeping the load constant. By taking the cooling medium flow rate and the vibration force as input variables and the temperature and the vibration amplitude as output variables, a coupled model is established to effectively depict the dynamic relationship between multiple physical quantities in the system and improve the explanation ability and dynamic prediction ability of the model.

[0027] 3. After completing the model construction, the application uses an observer to correct the real-time state and dynamically adjusts the cooling medium flow rate and the vibration force based on the predictive control algorithm, so that the temperature and the vibration amplitude tend to approach the target steady state level. This control strategy combines the advantages of model prediction and feedback observation, realizes dynamic regulation and control of the multivariable coupled system under different load conditions, and enhances the stability and response ability of the permanent magnet motor during operation. BRIEF DESCRIPTION OF DRAWINGS

[0028] The application will be further described below with reference to the accompanying drawings.

[0029] Figure 1 is a flowchart of a temperature and vibration amplitude monitoring and analysis control system of a permanent magnet motor according to the application. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0031] Please refer to Figure 1As shown, the application is a kind of permanent magnet motor temperature and vibration amplitude monitoring analysis control system, comprising:

[0032] Initial module: set a number of load nodes, flow rate nodes and vibration force nodes, group the flow rate nodes and vibration force nodes, keep the load of the permanent magnet motor reaching the load node i, and real-time obtain the temperature and vibration amplitude of the permanent magnet motor;

[0033] In a specific embodiment, according to the rated torque and the upper limit of the allowable overload of the permanent magnet motor, the output shaft torque is read in real time by the torque sensor, and the entire load interval is divided into a plurality of discrete load nodes at equal intervals or according to typical working condition density, for example, representative points such as no-load, light load, medium load, heavy load, etc. can be selected; the discrete nodes can cover the main working conditions while ensuring the operability of the test, so that the subsequent measured data has comparability;

[0034] Referring to the pumping capacity of the cooling circuit and the safety limit of the heat exchanger, the cooling medium flow rate is divided into a plurality of flow rate nodes between the minimum stable flow and the allowable upper limit; the external exciter of the machine base is divided into a plurality of vibration force nodes according to the vibration force within the safe amplitude range; the nodes are divided within the interval because fixed points facilitate the repeated application of the same physical quantity and avoid fluctuations caused by continuous adjustment;

[0035] The principle of "one flow rate node matching one vibration force node" is adopted for pairwise matching to generate a plurality of non-repeated groups; the matching mode usually corresponds to the flow rate node serial number and the vibration force node serial number one by one, or can use staggered or random matching, the purpose of which is to ensure that the two input variables appear in the form of independent combination during the test, facilitating the subsequent separation of coupling effects;

[0036] After completing the grouping, the motor and the loading device are closed-loop controlled to make the motor continuously maintain at the target load node i (i.e. any load node); the reason for closed-loop regulation is that only when the torque or current is stabilized at the target point can the temperature and vibration changes be caused only by the flow rate and vibration force combination and not be disturbed by the load fluctuation. When the load is stable, the flow rate of the cooling medium is set according to the current grouping and the output of the exciter is adjusted to the specified vibration force; the flow rate is controlled by the frequency conversion pump or the valve opening, and the vibration force is set by changing the eccentric mass or driving current of the exciter;

[0037] At this time, the thermistor embedded in the stator slot of the motor will convert the winding temperature into a voltage signal, which is sent to the data acquisition card in real time after signal conditioning; the three-axis acceleration sensor installed on the surface of the machine base converts mechanical vibration into a charge signal, which also enters the acquisition system after being processed by a charge amplifier. Since the temperature sensing element is in close contact with the winding and has small thermal inertia, the resistance value changes linearly with temperature, so it can reflect the thermal state in real time.

[0038] The model establishing module: when the temperature and the vibration amplitude reach a steady state, adjusting the flow rate of the cooling medium and the vibration force applied to the permanent magnet motor satisfies the grouping f1, the temperature and the vibration amplitude of the permanent magnet motor are acquired in real time until the temperature and the vibration amplitude reach a steady state again;

[0039] Adjusting the flow rate of the cooling medium and the vibration force applied to the permanent magnet motor to satisfy the remaining groupings, repeating the above steps;

[0040] In a preferred embodiment of the application, when the variance of the temperature of the continuous n temperatures is less than the preset temperature variance threshold, it is determined that the temperature reaches a steady state;

[0041] When the variance of the continuous n vibration amplitudes is less than the preset vibration amplitude variance threshold, it is determined that the vibration amplitude reaches a steady state;

[0042] It should be noted that if the variance of the continuous n vibration amplitudes or temperatures does not reach a steady state, an error message is sent for prompting, and η is a preset multiple and η≥5.

[0043] After acquiring the temperature and the vibration amplitude corresponding to all groupings, a state space model when the load reaches the load node i is constructed based on the subspace identification method;

[0044] In another preferred embodiment of the application, the space state model is:

[0045] ;

[0046] Wherein, x(k) represents a state vector at time point k, y(k) represents an output vector at time point k, and x(k+1) represents a state vector at the next time point adjacent to time point k;

[0047] Wherein, the state vector T(k) represents the temperature at time point k, and V(k) represents the vibration amplitude at time point k;

[0048] The state transition matrix a 11 , a 12 , a 21 , a 22 respectively represent a temperature self-attenuation coefficient, a vibration amplitude-temperature coupling coefficient, a temperature-vibration amplitude coupling coefficient, and a vibration amplitude self-attenuation coefficient;

[0049] The control input matrix b u 11, b u 12, b u 21, b u22 respectively represent the gain of the flow rate of the cooling medium on the temperature, the gain of the vibration force applied to the permanent magnet motor on the vibration amplitude, the gain of the vibration force applied to the permanent magnet motor on the temperature, and the gain of the flow rate of the cooling medium on the vibration amplitude;

[0050] Disturbance input matrix , b d1 , b d2 respectively represent the disturbance coefficient of the load of the permanent magnet motor on the temperature and the disturbance coefficient of the load of the permanent magnet motor on the vibration amplitude;

[0051] Output matrix , C 11 , C 12 , C 21 , C 22 are respectively 1, 0, 0, 1;

[0052] Control input vector , ΔF c (k), ΔF v (k) respectively represent the adjustment amount of the flow rate of the cooling medium at time point k, and the adjustment amount of the vibration force applied to the permanent magnet motor at time point k.

[0053] It should be noted that the state space model is a description method that unifies the internal state of a dynamic system at discrete sampling time, external input and measurable output into a first-order difference equation group, which originates from the concept of "state" in control theory: the behavior of any real system at a certain time actually depends on the energy accumulation, inertia or other storage effects it has experienced before, and these historical information can be compressed into a finite-dimensional vector-state vector. When the next sampling comes, only the state of the last step and the input applied in this step need to be known to completely predict the update of the system, which is the core of the state space idea.

[0054] In the present application, the state vector x(k) is directly selected as "motor winding temperature T(k)" and "machine base vibration amplitude V(k)", because both of them are not only the target quantities that need to be controlled ultimately, but also embody the internal thermal-mechanical coupling dynamics, and can fully represent the storage and interaction of system energy; the input vector u(k) is composed of "cooling medium flow rate adjustment amount ΔF c (k)" and "applied vibration force adjustment amount ΔF v (k)", and the two execution amounts are artificial controllable and have dominant influence on temperature and vibration; the load disturbance D is regarded as a background quantity that is difficult to adjust immediately and significantly affects the thermal-vibration level, and is incorporated into the model through an independent disturbance channel B d , so as to clearly distinguish between controllable and uncontrollable sources;

[0055] Therefore, the model is configured as:

[0056] ;

[0057] Matrix A reflects the "intrinsic memory" laws governing temperature self-dissipation, vibration self-damping, and their coupling; Matrix B... u The immediate gain and time-delay coupling effects of flow velocity and vibrational force on temperature and vibration are described; B d This quantifies the direct impact of load changes on the two states; C is an identity matrix, meaning the measured value is the state itself; A, B u and B d It is obtained based on subspace identification, and will not be elaborated here;

[0058] Its construction principle is as follows:

[0059] 1) Temperature and vibration are measured by sensors at fixed sampling intervals. Since thermal inertia and mechanical vibration decay can be approximated linearly on this time scale, a discrete-linear model can be used to obtain sufficient accuracy, thus avoiding the complexity of solving differential equations.

[0060] 2) To make matrices A, B, B d To accurately reflect the actual mechanism, this scheme applies pseudo-random binary sequence (PRBS) excitation to the flow velocity and vibration force while keeping the load constant. PRBS has the characteristics of uniform spectral energy, finite amplitude and easy generation. It can fully excite all dynamic modes of the system within a safe range. The collected input-output sequence is organized into a Hankel matrix. The finite-order state space structure of the system can be directly estimated through singular value decomposition without prior order selection or solving high-order polynomials.

[0061] 3) Because the load remains constant during the testing phase, B d The channel can obtain a set of calibration values ​​through multi-load node experiments, and then substitute the load as a known quantity into the model during real-time operation to explicitly remove the load's influence, allowing the controller to focus on compensating for the controllable part of the flow velocity and vibration force on the temperature and vibration state.

[0062] This state-space-based recursive approach maintains high tracking accuracy and robustness in multivariable coupled permanent magnet motor systems with disturbances. The fundamental reason is that the model preserves the essential dynamics of the physical process (matrices A, B). u and B d The structure and digital quantification of thermal paths, mechanical coupling, and control channels are used, and online observers are used to continuously calibrate unknown disturbances and model uncertainties, thereby generating timely and coordinated flow velocity and vibration force adjustment commands under any given load node, achieving a dynamic balance between temperature and vibration objectives.

[0063] The adjustment module takes the state space model corresponding to the current load D1 of the permanent magnet motor as a target model, inputs the current load D1, temperature D2, vibration amplitude D3, flow rate D4 of the cooling medium and vibration force D5 into the target model, and outputs a state vector Z1. The temperature and vibration amplitude of the permanent magnet motor are adjusted based on the state vector Z1 to reach preset normal temperature N1ys and normal vibration amplitude N2ys, respectively.

[0064] In a specific embodiment, when the permanent magnet motor is running, a torque sensor installed on the transmission chain is used to calculate the mechanical load on the output shaft in real time. The reading is converted into an equivalent load coefficient and named D1. Torque is used instead of current to represent the load because torque can directly reflect the output power of the motor and is less affected by factors such as power grid fluctuations and temperature rise resistance changes, and can more accurately represent the electromechanical coupling state.

[0065] Among the pre-stored multiple sets of state space models, the set of parameter matrices closest to the current D1 is searched. If D1 is located between two discrete load nodes, linear interpolation is performed on the adjacent two sets of models according to the load ratio to ensure that the model coefficients change continuously with the load. It can be understood that in the identification stage, an independent model is obtained for each load node. Linear interpolation can maintain the monotonic change of the dynamic matrix with the load within the interval, avoiding the control discontinuity caused by step changes.

[0066] The selected or interpolated matrix set is regarded as a target model to describe the current thermal-vibration dynamics. Then, the winding temperature of the permanent magnet motor is collected as D2, the three-axis vibration sensor output of the motor frame is integrated into D3, the cooling circuit flowmeter output is converted into D4, and the current excitation mass or current from the excitation driver unit is fed back to determine D5. D4 and D5 are regarded as controllable inputs because the flow rate of the cooling medium affects the heat exchange coefficient, and the vibration force affects the mechanical energy injection, and the two work together to produce independent adjustable driving in the thermal and vibration channels.

[0067] D1 is taken as an external disturbance, D4 and D5 are taken as control input, and D2 and D3 are taken as the state quantities observed in the previous step. They are all substituted into the discrete equation of the target model: the temperature and vibration states are multiplied by their own decay coefficients and coupling coefficients in the matrix operation, and the cooling flow rate, vibration force gain term and load disturbance term are added to complete one forward recursion. The matrix multiplication and addition process is essentially a first-order linear approximation of energy balance and inertial coupling, which clearly expresses the causal relationship between internal heat accumulation, mechanical vibration storage and external action. After the recursion, the predicted state vector Z1 of the next sampling period is obtained, which contains the new estimated values of temperature and vibration. These values maintain the coherence of the physical model and incorporate real-time measurement information, so they can be used as the basis for subsequent observer correction and predictive control algorithm.

[0068] In another preferred embodiment of the present application, adjusting the temperature and vibration amplitude of the permanent magnet motor to reach the preset normal temperature N1ys and normal vibration amplitude N2ys respectively comprises:

[0069] After the model is recursively derived to obtain the predicted state vector Z1, the state observer is used for correction first: the observer compares the predicted temperature and vibration value in Z1 with the real-time measured temperature and vibration by the sensor, deduces the model error or measurement noise source using the difference between the two, and injects the part of deviation into Z1 according to the observability weight of the system dynamics to obtain the target vector which is closer to the real operating condition through updating.

[0070] The target vector contains two components of temperature N1 and vibration amplitude N2, and the system directly extracts the two from the target vector, and then obtains the temperature difference N1' and vibration difference N2' by subtracting the preset normal level N1ys and N2ys respectively; through the calculation of the difference, the information of "how far from the target" can be quantified explicitly, which provides the direction for the next control decision.

[0071] Based on the model predictive control idea, the state vector just corrected is taken as the current starting point, N1' and N2' are taken as the performance index of future behavior, the target model is used to deduce the possible trajectory of temperature and vibration in the prediction interval, and the error and the cost of operation change are accumulated on each trajectory, and a set of optimal future cooling flow rate and vibration force adjustment sequence is obtained by solving; the model predictive control first looks into the future before acting in principle, and all the limited dynamics and coupling are included in the planning, which can minimize the temperature deviation and vibration deviation at the same time under the condition of guaranteeing the physical constraints; the controller finally implements the flow rate and vibration force command of the current step, and then observes and optimizes again when the next sampling period comes, and so on, which iterates, and with the help of model accurate prediction and real-time feedback double information, the temperature and vibration are constantly converging to the target N1ys and N2ys.

[0072] It should be noted that the normal temperature N1ys and the normal vibration amplitude N2ys change based on the change of the load.

[0073] Specifically, in the calibration stage, the allowed working load is evenly divided into several discrete nodes from no load to the upper limit of the rated load, the motor is stably operated to the thermal-vibration steady state at each node, and the steady state temperature and vibration amplitude are recorded as reference samples point by point;

[0074] The load node is regarded as the independent variable, and the corresponding steady state temperature or vibration is regarded as the dependent variable, and a function relationship is established respectively, which is fitted based on the above samples and will not be described here; in real-time operation, the current measured load D1 is substituted into the above function relationship to calculate the corresponding N1ys and N2ys.

[0075] The above formulas are all dimensionless values calculated, the formulas are obtained by collecting a large amount of data to simulate a formula of the most recent real situation, and preset parameters and threshold values in the formulas are set by a person skilled in the art according to actual conditions.

[0076] The above has carried out the detailed explanation to one embodiment of the application, but the content described is only the preferred embodiment of the application, cannot be considered for limiting the implementation range of the application. All equivalent changes and improvements made according to the scope of the application are still within the scope of the application.

Claims

1. A monitoring, analysis, and control system for the temperature and vibration amplitude of a permanent magnet motor, characterized in that, include: Initial module: Set up several load nodes, flow velocity nodes and vibration force nodes, group the flow velocity nodes and vibration force nodes, keep the load of the permanent magnet motor at load node i, and obtain the temperature and vibration amplitude of the permanent magnet motor in real time; Model building module: When the temperature and vibration amplitude reach a steady state, adjust the flow rate of the cooling medium and the vibration force applied to the permanent magnet motor to meet the grouping f1, and obtain the temperature and vibration amplitude of the permanent magnet motor in real time until the temperature and vibration amplitude reach a steady state again. Adjust the flow rate of the cooling medium and the vibration force applied to the permanent magnet motor to satisfy the remaining groups, and repeat the above steps; after obtaining the temperature and vibration amplitude corresponding to all groups, construct the state space model when the load reaches the load node i based on the subspace identification method. Adjustment module: Based on the state-space model, adjust the temperature and vibration amplitude of the permanent magnet motor to reach the preset normal temperature N1ys and normal vibration amplitude N2ys, respectively.

2. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 1, characterized in that, Grouping of velocity nodes and vibration force nodes includes: Several load nodes, flow rate nodes, and vibration force nodes are set in the preset load range, cooling medium flow rate range, and vibration force range, respectively. A group includes a velocity node and a vibration force node, and the velocity node and / or vibration force node are different in different groups.

3. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 1, characterized in that, When the variance of n consecutive temperatures is less than a preset temperature variance threshold, the temperature is determined to have reached a steady state. When the variance of n consecutive vibration amplitudes is less than the preset vibration amplitude variance threshold, the vibration amplitude is determined to have reached a steady state.

4. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 3, characterized in that, If the variance of vibration amplitude or temperature fails to reach steady state for ηn consecutive vibrations, an error message will be sent to indicate this, where η is a preset multiple and η≥5.

5. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 1, characterized in that, Adjusting the temperature and vibration amplitude of the permanent magnet motor to achieve the preset normal temperature N1ys and normal vibration amplitude N2ys respectively includes: The state space model corresponding to the current load D1 of the permanent magnet motor is used as the target model. The current load D1, temperature D2, vibration amplitude D3, flow rate of cooling medium D4 and vibration force D5 of the permanent magnet motor are substituted into the target model to output the state vector Z1. Based on the state vector Z1, the temperature and vibration amplitude of the permanent magnet motor are adjusted to reach the preset normal temperature N1ys and normal vibration amplitude N2ys, respectively.

6. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 5, characterized in that, Adjusting the temperature and vibration amplitude of the permanent magnet motor to achieve the preset normal temperature N1ys and normal vibration amplitude N2ys also includes: The target vector is obtained by correcting the state vector Z1 using a state observer. Extract the temperature N1 and vibration amplitude N2 from the target vector, and calculate the temperature difference N1'=N1-N1ys and the vibration amplitude difference N2'=N2-N2ys; Based on the MPC algorithm and the temperature difference and vibration amplitude difference, the temperature and vibration amplitude are guaranteed to reach the preset normal temperature N1ys and normal vibration amplitude N2ys, respectively.

7. The temperature and vibration amplitude monitoring and control system for a permanent magnet motor according to claim 1, characterized in that, Normal temperature N1ys and normal vibration amplitude N2ys vary based on the load.

Images