7922results about "Dynamo-electric converter control" patented technology

The invention provides a brushless motor attitude detection and balance control method and system based on a gyroscope, and relates to the technical field of control, and the method comprises the steps: collecting angular velocity and acceleration data through a six-axis gyroscope, carrying out the noise reduction through wavelet transform, and carrying out the attitude calculation through the combination of an extended Kalman filter and a quaternion algorithm. A rotor position signal is obtained through a magnetic encoder, nonlinear compensation is carried out, and rotating speed data are calculated. A motor state is modeled by adopting a long-short-term memory network, a double-layer adaptive fuzzy neural network controller is constructed, and attitude error compensation and rotation speed fluctuation suppression are realized. A controller model is optimized through particle swarm optimization and a genetic algorithm, a compensation current vector is corrected in real time, and the control precision and stability of the brushless motor are improved. According to the method, the operation efficiency and the dynamic response capability of the brushless motor are effectively improved.

The invention relates to the technical field of motor control, and discloses a brushless motor adaptive control method and system based on artificial intelligence, and the method comprises the steps: collecting the multi-point temperature data of a motor, building a thermal dynamic model, and reconstructing the complete temperature field distribution; identifying a relation function between motor parameters and temperature, and establishing a temperature sensitive parameter model; in combination with temperature field distribution and a temperature sensitive parameter model, learning long-term influence of control actions on temperature distribution, and predicting temperature evolution trends under different control strategies; constructing a multi-objective optimization control strategy, and generating a motor control instruction and a heat dissipation control instruction; dynamically selecting an optimal heat dissipation strategy combination according to the generated control instruction, the current working condition and the predicted heat influence; according to the invention, high-precision control and thermal management optimization of the brushless motor in a temperature change environment are realized.

The invention relates to the field of mine ventilation, in particular to an intelligent adjusting method and system for mine ventilation. The method comprises the following steps: constructing a dynamic topology model taking a roadway as an edge and taking a fan and an air door as nodes based on a mine CAD drawing; acquiring the actual wind pressure and the actual wind volume of each roadway branch in real time, performing inversion to obtain the current wind resistance, and updating the wind resistance attribute of the edge in the dynamic topology model by using the current wind resistance; calculating the optimal air volume of the roadway branch by using the updated dynamic topology model; based on the optimal air volume, target regulation and control parameters of the draught fan and the air door are obtained through solving by means of a particle swarm algorithm; and according to the target regulation and control parameters, the fan and the air door are adjusted through a fuzzy PID algorithm. The problem that in the prior art, mine ventilation adjustment is not intelligent and safe enough is solved, the theoretical optimal air volume is obtained through deep analysis of the mine, then ventilation adjustment is conducted step by step, and the scientificity and efficiency of ventilation adjustment are improved.

The invention discloses a motor control method and device based on an encoder, a medium and a program product, and relates to the field of motor control, and the method comprises the steps: receiving a position signal and a speed signal outputted by the encoder, and carrying out the filtering processing to obtain an operation state parameter; collecting mechanical vibration and electromagnetic noise generated in the operation process of the motor to obtain acoustic parameters of the motor, and extracting frequency characteristic parameters representing the rotating speed and motion characteristics of the motor; performing data fusion on the operation state parameters and the frequency characteristic parameters according to a preset weight to generate an operation state model; the operation state model is compared with a standard motion trail, and the position deviation value and the speed deviation value of the actual motion trail of the motor are calculated; and calculating a compensation control quantity according to the position deviation value and the speed deviation value, converting the compensation control quantity into a driving signal and outputting the driving signal to a motor driver so as to drive a motor to perform operation adjustment. According to the invention, the control precision of the motor in actual operation can be improved.

The invention discloses a dual-electric brake boosting system, which belongs to the technical field of vehicle brake control and comprises the following steps: S1, dynamically calculating quadrature-axis inductance parameters, generating a synchronous magnetic field signal and inhibiting electromagnetic interference of dual motors; s2, extracting a harmonic-rotating speed mapping relation, and dynamically correcting an observation equation to control a parameter error; s3, reconstructing neutral point voltage to counteract high-frequency jitter, and reducing residual harmonic interference through adaptive filtering; s4, establishing a three-dimensional thermal field to predict copper and iron loss, dynamically adjusting current and generating an inverse time limit protection curve; s5, splitting the hot parameters into parity check frames, optimizing a communication protocol and compressing a refresh cycle to 10ms; s6, overlapping response of the white noise excitation system, and performing closed-loop calibration on the filtering weight to improve the observation precision; s7, triggering an audible and visual alarm and synthesizing a directional voiceprint and a tactile pulse to ensure safety regulations and perception intensity; the method has the beneficial effects that the method has remarkable advantages in a high-temperature and high-vibration severe environment, and the reliability and the safety of a system can be improved.

The invention provides an unmanned aerial vehicle motor rotating speed control method based on active disturbance rejection. The method comprises the following steps: 1) measuring the rotating speed of a motor by adopting a high-precision rotating speed sensor based on a quantum effect; 2) designing a tracking differentiator TD to smooth an expected rotating speed, and outputting a rotating speed tracking signal and a rotating speed tracking signal change rate; 3) introducing a dynamic weight matrix to form a dynamic weight expansion state observer DWESO, and taking an output state variable estimation value and a total disturbance estimation value as the input of the NLSEF; 4) automatically searching the optimal combination of the gain parameters of the DWESO by adopting an ALA (artificial Louver Mouse Algorithm), so that the optimal state variable estimation value and the optimal total disturbance estimation value are output to the NLSEF; compared with the prior art, the method for controlling the rotating speed of the unmanned aerial vehicle has the advantages that the dynamic response speed, the anti-jamming capability and the parameter adaptability of the system are remarkably improved, and the flight performance and the robustness of the unmanned aerial vehicle are improved.

The invention relates to a dual three-phase permanent magnet synchronous generator rectification system and a direct current voltage stabilization control method thereof. Comprising a dual three-phase permanent magnet synchronous generator, a VSD decoupling converter, a load current observer, a dynamic load feed-forward compensator, a voltage closed-loop controller, a dead-beat predictive current controller, a maximum four-vector SVPWM modulation module and a six-phase rectifier. The double-three-phase topological structure adopted by the invention has the advantages of multiple control degrees of freedom, high reliability and the like. A dynamic load feed-forward compensator is constructed to perform dynamic feed-forward compensation on quadrature-axis current of the motor, so that the recovery time of bus voltage is shortened, and the voltage fluctuation amplitude is reduced; the designed dead-beat predictive current controller optimizes the dynamic characteristics of a current loop, improves the torque tracking performance of the motor, and further improves the voltage stabilization regulation capability of the system. The designed load current observer realizes the analysis redundancy of current detection and improves the reliability of the system.

The invention provides a wide-voltage self-adaptive closed-loop vector swimming pool pump anti-interference method, and relates to the technical field of motor control and power electronics, and the method comprises the steps: collecting three-phase power supply voltage fluctuation characteristic parameters and motor operation state parameters in real time; performing amplitude compensation and phase synchronization correction on the voltage parameter based on the dynamic voltage compensation factor; a closed-loop vector anti-interference control model is constructed, and model parameters are adjusted in real time through a vector immunity coefficient; dynamically correcting control output by adopting a multivariable feedback regulation mechanism; executing an anti-interference instruction and synchronously updating PWM modulation parameters, and verifying a control effect in combination with hardware-in-the-loop simulation; and parameter self-learning optimization is realized through a genetic algorithm. The dynamic anti-interference capability under power grid voltage fluctuation and harmonic interference is improved, intelligent thermal management is realized through a temperature-voltage-current multi-dimensional coupling model, full-life-cycle self-adaptive optimization of the system is guaranteed, and the problems of compensation lag, insufficient harmonic suppression and poor long-term stability are effectively solved.

The invention discloses a multi-cycle prediction compensation method for a servo motor based on an M3 kernel, and belongs to the technical field of industrial automation control, and the method comprises the steps: obtaining real-time operation parameters of the servo motor, carrying out the compensation for the rapid change of the servo motor, and generating a short-cycle prediction compensation amount; generating a long-period prediction compensation amount by analyzing a long-period operation rule of the servo motor; generating an instantaneous confidence coefficient according to the real-time operation parameters and the short-period prediction compensation amount, and generating a trend confidence coefficient based on historical precision data of the long-period prediction compensation amount; and calculating a dynamic weight according to the instantaneous confidence coefficient and the trend confidence coefficient, carrying out fusion processing on the short-period prediction compensation amount and the long-period prediction compensation amount, generating a final compensation instruction, and superposing the final compensation instruction to an output end of a servo motor control ring. According to the method, disturbance is processed by constructing short-period and long-period prediction with differential precision in parallel, and the dynamic response speed and tracking precision of the servo system can be remarkably improved.

The invention relates to the technical field of motor control, and discloses a permanent magnet synchronous motor control system and method for an electric drive hydraulic source, and the system comprises a data collection module which is used for collecting the state parameters of the electric drive hydraulic source and the operation data of a permanent magnet synchronous motor in real time through multiple sensors; the sensor redundancy and fault-tolerant module is used for performing parallel sampling through hardware dual-redundancy configuration and dual sensors; the self-adaptive fuzzy logic control module is used for dynamically adjusting a rotating speed instruction and a torque instruction of the permanent magnet synchronous motor based on the collected state parameters; a data driving optimization module; and a digital twinning prediction maintenance module. A self-adaptive fuzzy logic control module is used for dynamically generating a motor rotating speed and torque instruction based on parameters such as real-time pressure, flow deviation and change rate, a fuzzy logic algorithm is used for processing a nonlinear time-varying load and quick response, a self-adaptive fuzzy logic control rule weight and a power conversion circuit parameter are optimized through a reinforcement learning algorithm, and the control precision is improved. And dynamic self-optimization of permanent magnet synchronous motor control is realized.

Disclosed in the present invention are a dual three-phase asymmetric stator-type double-permanent-magnet vernier electric motor and an improved model predictive current control method therefor. The electric motor comprises a stator core, stator permanent magnets, a rotor core and a rotor ferrite, wherein the stator core is formed by alternately arranging umbrella-shaped armature teeth and quasi-rectangular armature teeth in the circumferential direction, the stator permanent magnet, which is magnetized radially outwards, is adhered to each of openings on two sides of the umbrella-shaped armature teeth, and a fan-shaped auxiliary slot is formed between the umbrella-shaped armature teeth and the stator permanent magnet; and the shape of the rotor core is similar to a gear, the rotor ferrite is embedded in the rotor core using a Halbach-based alternating-pole array, and the length of the rotor ferrite is greater than the length of the rotor core and the length of the stator core. In addition, the present invention uses a model predictive current control system based on a virtual voltage vector to construct a cost function to select the voltage vector having the minimum switching frequency, and make same operate preferentially. The present invention not only improves the torque density of the electric motor, but also significantly reduces switching losses in model predictive control.

The invention relates to the technical field of motor control, and particularly provides a permanent magnet synchronous motor current harmonic disturbance suppression method and a motor system.The permanent magnet synchronous motor current harmonic disturbance suppression method comprises the steps that firstly, a permanent magnet synchronous motor mathematical model considering harmonic disturbance under the d-q axis of a synchronous rotating coordinate system is constructed, and a theoretical basis is provided for subsequent control strategy design; an improved resonance controller is set and embedded into the extended state observer, comprehensive estimation of d-q axis non-periodic disturbance and periodic harmonic disturbance is achieved, finally, an enhanced current loop active disturbance rejection controller based on the improved resonance-extended state observer is built, unexpected peak values are eliminated, and the disturbance rejection rate of the current loop is improved. And comprehensive suppression of aperiodic disturbance and periodic disturbance is realized. According to the method, aperiodic and periodic disturbance can be suppressed, unexpected peak values are eliminated, system instability caused by noise amplification is avoided, and the steady-state performance and robustness of current control of the permanent magnet synchronous motor are remarkably improved.

The invention relates to the technical field of motor control, in particular to a permanent magnet synchronous motor online parameter identification system and a compensation method thereof, comprising a data acquisition module, a deep transfer learning parameter identification module, a parameter optimization module, a temperature compensation module and a controller parameter integration module. The deep transfer learning parameter identification module establishes mapping and function relations between characteristic factors and motor parameters through a teacher network, a transfer network, a memory network and an output layer, processes time sequence information and outputs a parameter identification result, and the parameter optimization module finely adjusts the parameters based on a particle swarm optimization algorithm. The temperature compensation module carries out temperature compensation on the optimized parameters according to a temperature distribution model, the controller parameter integration module generates control parameters, and the motor control module generates torque control signals according to the control parameters, so that fusion processing of multi-physical field characteristics is realized, and the precision and adaptability of parameter identification are greatly improved; and the d-q axis inductance identification error is reduced by more than 70%, and the millihenry-level precision is achieved.

The invention provides a magnetic sensor control system with original point positioning and limiting functions, and relates to the technical field of data processing, and the system comprises a dynamic magnetic field tracking module which is used for receiving real-time magnetic field data detected by a magnetic sensor, setting reference magnetic field data, and calculating a first difference value between the real-time magnetic field data and the reference magnetic field data; the trend deviation correction module is used for carrying out sliding statistics to form an error change curve and selecting a main correction function from a preset error change function group through goodness of fit evaluation; generating an offset compensation amount according to the predicted value of the main correction function, and dynamically adjusting the reference magnetic field data; the positioning verification module is used for calculating a second difference value in combination with the current real-time magnetic field data and performing judgment; the limiting judgment control module is used for sending a stop control instruction to the motor driving module when the successful signal is judged; according to the invention, autonomy and accuracy of magnetic sensor control are improved.

The invention provides a multi-mode control method and system for a brushless doubly-fed motor, and relates to the technical field of motor control, and the method comprises the steps: extracting torque-rotating speed slopes and dynamic response time constants of two points based on a steady-state working point of a current mode and an expected working point of a target switching mode, and constructing a linear correction function; fusing an output value of the linear correction function with an optimization result to generate a modal transition compensation coefficient, and injecting the compensation coefficient into a rotor side voltage control ring based on a feedforward control channel to generate an anti-disturbance dynamic compensation control strategy; and for a non-smooth adjustment item in the dynamic compensation control strategy, performing smoothing processing on a discontinuous boundary of a control quantity by adopting a subgradient projection algorithm, verifying continuous conductivity of a control curved surface in combination with a Lyapunov stability criterion, and generating a final control instruction. According to the invention, adaptive smooth switching control of the brushless doubly-fed motor can be realized.

The invention belongs to the technical field of permanent magnet synchronous generator demagnetization fault detection, and particularly discloses a permanent magnet motor fault early warning system based on big data, which comprises a high-frequency injection and grid-connected control module, a fault early warning module and a fault early warning module, actively injecting a high-frequency disturbance signal of which the frequency is higher than the fundamental frequency into a control loop of the permanent magnet synchronous generator; the multi-source synchronous acquisition module is used for synchronously acquiring multi-dimensional operation parameters of the permanent magnet synchronous generator and performing time domain alignment and frequency domain separation on the multi-dimensional operation parameters to obtain synchronous acquisition signals; the composite feature extraction module is used for extracting a multi-dimensional demagnetization criterion of the permanent magnet synchronous generator based on the synchronous acquisition signal; the self-adaptive threshold regression prediction module is used for performing fusion evaluation on the multi-dimensional demagnetization criteria by using the demagnetization health index model to generate a demagnetization judgment result of the demagnetization degree of the permanent magnet synchronous generator; the method has the advantages that the demagnetization recognition accuracy is improved, and early warning is achieved.

The invention relates to the technical field of industrial automation control, and discloses a water-based paint production and processing equipment control system, which comprises the following steps: acquiring stator current and rotor angular velocity, and reconstructing total load torque by using a sliding mode algorithm; extracting an input power low-frequency component to construct a heat dissipation slow manifold, and calculating a thermal drift disturbance component and an orthogonal residual component through orthogonal projection; on the basis of a two-component generation superposition instruction closed-loop adjustment driving mechanism, a double-time-scale orthogonal projection mechanism is utilized, non-structural thermal drift interference is automatically stripped under the condition that heat transfer parameters of equipment do not need to be predicted, the problem of control divergence caused by model parameter mismatch is solved, and decoupling control over the real rheological state of materials is achieved.

The invention belongs to the field of computer vision, and particularly relates to a method, a device and a system for monitoring suction-scrabbling falling of a cleaning robot, and the method comprises the following steps: 1) a rear-view camera arranged on the cleaning robot collects suction-scrabbling images, and carries out data labeling; 2) building a deep learning labeling and training environment in a server or a workstation, selecting a YOLOv8 target detection network model, sending labeled suction and scrabbling image data into the model for training, and performing format conversion and quantization on the model after the training is completed; 3) inputting an image acquired in real time into the trained target detection model, and judging whether the suction rake falls off or not; (4) if the suction scrabbling device falls off, the upper computer sends falling abnormal information to a robot controller of the cleaning robot, and the robot controller controls a hub motor to brake emergently; and meanwhile, the upper computer transmits the abnormal information of the suction-scrabbling falling and the position coordinate information of the robot in the global map to the operation and maintenance personnel through the cloud platform and then transmits the abnormal result and the position information of the suction-scrabbling falling to the operation and maintenance personnel.

The invention relates to the technical field of motor control, in particular to a control and parameter intelligent optimization method for an anti-impact high-precision PMSM (permanent magnet synchronous motor) feeding servo system, which comprises the following steps of: S1, establishing a physical structure and a dynamic model of a PMSM driving feeding system; s2, designing a variable gain fractional order super-spiral sliding mode controller VGFSTSMC, realizing finite time convergence of position tracking errors by dynamically adjusting and controlling gain coefficients, and inhibiting system jitter; s3, designing an adaptive sliding mode disturbance observer ASMDO, and estimating and compensating unknown disturbance in real time through adaptive gain adjustment and an integral sliding mode surface; s4, identifying a system Stribeck friction model based on a least square method, and inputting the system Stribeck friction model as a friction feedforward compensation FFC to a current loop to reduce the disturbance uncertainty of the system; s5, dynamically adjusting and optimizing control parameters of the VGFSTSMC and the ASMDO by adopting an optimization algorithm so as to minimize a root-mean-square value RMSE of a position tracking error and a maximum instantaneous error; and S6, VGFSTSMC, ASMDO and FFC are combined with an optimization algorithm, and the PMSM is driven to realize high-precision position control.

The invention provides a transient current capability improvement control system and method of a wind and light power generation system. The system comprises a self-synchronizing voltage source control module, a junction temperature prediction module, a transient current improvement control module, a current instruction calculation module and a transient current precise control module. According to the invention, online observation of the junction temperature of the wind-solar converter power device can be realized, the maximum short-circuit current which can be output can be accurately predicted, the DC bus voltage, the switching frequency and the modulation strategy are adjusted when the power grid has a fault, the junction temperature of the power device is reduced, and the transient current endurance capability of the power device is improved. And the transient current is accurately controlled to limit the utilization of the transient capability of the power device.

The invention discloses a six-winding high-voltage variable-frequency speed regulation control method and system, and belongs to the technical field of high-voltage variable-frequency speed regulation, and the method comprises the steps: building an electric-thermal-magnetic coupled six-dimensional nonlinear system model through collecting the structural parameters, thermosensitive data and an initial state of a motor; establishing a frequency domain regulation and control matrix among the six windings in combination with the operation condition and the load type; predicting a future disturbance power trend by using a weighted short-time Fourier analysis method, dynamically correcting the reference current of each winding, and generating six groups of PWM control signals; when the performance of the winding is degraded, fault-tolerant topology reconstruction and driving task redistribution are executed; periodically reconstructing a control matrix through a thermoelectric feedback mechanism, and executing parameter adaptive optimization according to a current balance coefficient and hot redundancy distribution; according to the method, high-precision current coordination control, frequency domain energy decoupling and winding thermal load balancing can be realized, and the speed regulation response speed, the stability and the fault-tolerant capability of the system are remarkably improved.

The invention discloses an error compensation method for a dead-beat predictive current control model of a high-speed permanent magnet synchronous motor in a static coordinate system. The method comprises the following steps: firstly, analyzing a dead-beat predictive current control scheme of the high-speed permanent magnet synchronous motor under a static coordinate system, and on the basis, analyzing a steady-state current control error caused by parameter mismatch, transient current tracking, voltage loss caused by nonlinearity of an inverter, and current errors in a steady state and a transient state; and an error compensation scheme based on dead-beat predictive current control of the high-speed permanent magnet synchronous motor under a static coordinate system is provided, namely, self-adaptive reference correction current injection is provided. According to the method, the parameter robustness of dead-beat predictive current control of the high-speed permanent magnet synchronous motor based on static coordinates is effectively improved, and steady-state current errors caused by inaccurate models can be effectively eliminated.

The invention discloses a current harmonic disturbance suppression method and suppression system for a permanent magnet synchronous motor. The method comprises the following steps: acquiring voltage and current signals of an electrical loop phasor test in the operation of the motor; an inductance identification algorithm based on high-frequency response is adopted, high-frequency excitation signals are injected, current response is monitored, and stator inductance parameters are calculated; constructing a multi-synchronous rotating coordinate system based on the parameter, and decomposing the current signal to obtain each harmonic current component; building a fuzzy full-order sliding mode observer, inputting an inductance parameter, voltage data and a harmonic current component, and dynamically adjusting a sliding mode surface parameter to observe the position and the rotating speed of a rotor; independently controlling each harmonic current adjusting channel under a multi-coordinate system in combination with observation information, and generating a compensation control signal; and the synthesized master control signal is output to the driving circuit. The system comprises six units, and the method and the system can accurately obtain parameters, efficiently decompose harmonic waves, accurately observe states, realize multi-frequency harmonic disturbance suppression, and improve motor operation stability and efficiency.

The invention discloses a multi-axis motor control system based on an ARM and an ASIC, and particularly relates to the technical field of multi-axis motor control, and the system comprises a control processing module, a real-time execution module, a state mirror image construction module and a path compensation module. The control processing module generates a target trajectory in combination with a multi-axis task and spatial constraints, and constructs a prediction model; the real-time execution module realizes multi-axis synchronous control through a hardware sequencer; the state mirror image construction module maintains a difference state of feedback and prediction in real time; the path compensation module dynamically calls candidate track fragments according to the difference vector when the path compensation module is abnormal, and path self-recovery is completed; according to the method, the multi-axis path synchronization precision is improved, the intelligent selection and space adaptation capability of path compensation is enhanced, meanwhile, a feedback anomaly recognition and fault-tolerant control mechanism in an interference state is provided, the track continuity in a cabin complex environment and the stability of a control system are ensured, and the comprehensive effects of high precision, high robustness and uninterrupted operation are achieved.

The invention relates to the technical field of servo control, in particular to a high-precision current closed-loop control system and method for a servo driver, and the method comprises the steps: collecting three-phase current, rotor position, winding temperature and bus voltage, and constructing a state data set; constructing a parameter identification model fusing physical prior and an attention mechanism, deducing inductance and flux linkage parameters influenced by temperature, saturation and cross coupling, and correcting a motor model in real time; the correction parameters are injected into an FOC decoupling and feedforward link, and a self-adaptive PI regulator is linked to set the gain of a current loop on line; calculating a d-q axis voltage command according to the update model to respectively control excitation and torque components; an extended state observer is introduced to estimate load abrupt change and parameter disturbance, feed-forward compensation is carried out, and three-phase PWM is generated through anti-Parker and SVPWM; and an inverter nonlinear compensation model of a dead zone and switch delay is constructed, PWM is pre-distorted and output to a power device, and robust and low-ripple current closed-loop control of the servo motor is realized.

The invention relates to the technical field of mining permanent magnet synchronous motor sensorless control, and particularly discloses a composite sliding mode control and adaptive phase-locked loop collaborative optimization method. Aiming at the technical bottlenecks of a traditional control strategy in the aspects of rotating speed fluctuation suppression, load disturbance compensation and rotor position observation precision, a collaborative architecture of a time-varying integral terminal sliding mode control module, a sliding mode disturbance observation module and a self-adaptive phase-locked loop module is constructed, so that the dynamic performance optimization of the system is realized. According to the method, through the dynamic coupling design of the time-varying gain nonlinear reaching law and the fast integral terminal sliding mode surface, the convergence speed and the buffeting suppression requirement are balanced while the disturbance dynamic influence is eliminated; multi-dimensional decoupling observation of external load disturbance is realized based on a hierarchical disturbance observer architecture, and a disturbance real-time suppression path is established in combination with a feed-forward compensation strategy; and constructing an error self-adaptive correction mechanism of rotor position observation by dynamically adjusting a phase-locked loop proportionality coefficient and a phase compensation parameter. The limitation of parameter solidification and observation coupling in traditional control is broken through, the rotating speed tracking stability, the position observation precision and the anti-interference capability under complex working conditions are remarkably improved, and an innovative solution is provided for a high-precision servo driving system.

The invention relates to the technical field of inverter power control, and discloses a given current-based inverter power control method and system, and the method comprises the steps: calculating a fluctuation compensation parameter based on a bus voltage, and carrying out the real-time compensation of a q-axis basic current, and obtaining a first given q-axis current; predicting the bus voltage of the next period and correcting the first given q-axis current in advance to obtain a second given q-axis current; on the basis of the stator voltage saturation state, weak magnetic d-axis current given is generated, low-pass filtering is carried out on the second q-axis current given and the weak magnetic d-axis current given, and a d-axis current instruction and a q-axis current instruction are obtained; a PWM driving signal corresponding to a dq-axis current instruction is generated, an inverter switch is controlled, meanwhile, a power deviation signal is collected to update q-axis basic current, accurate prediction of bus voltage and advanced correction of given current are achieved, compared with traditional lag compensation, the dynamic response is faster, and the power control precision and the operation stability are improved.

The invention discloses an IADRC and torque compensation fused PMSM speed regulation control method. The method comprises the steps of establishing a mathematical model of a surface-mounted permanent magnet synchronous motor in a rotating coordinate system; an improved Luenberger load torque observer is designed; designing an active disturbance rejection controller; designing an improved super-spiral sliding mode algorithm; and designing an improved speed loop active disturbance rejection controller. The improved Luenberger observer identifies the load torque of the system in real time, and parameters obtained through identification are compensated to the improved active-disturbance-rejection controller, so that system oscillation caused by load change is avoided; a traditional non-linear state error feedback control rate in active disturbance rejection control is combined with a super-spiral sliding mode algorithm, and a new piecewise function is designed and applied to a sliding mode reaching law. According to the method, the response speed and the working efficiency of the system are effectively improved, meanwhile, the anti-interference performance of the system is enhanced, and the robustness of the system is improved.

A propulsion system, comprising: a motor assembly including a stator and a rotor, a heat exchanger configured to receive air to cool a liquid, and a thermal plate including one or more channels configured to convey the liquid from the heat exchanger to the motor assembly. The heat exchanger is mechanically and fluidically coupled to the thermal plate.

According to the step motor sensorless control method based on improved robust Kalman filtering, an HBM current state equation is established, and an extended Kalman state equation is established; establishing an inductance deviation model, and deducing a system covariance matrix with errors; parameter uncertainty robust control is introduced, an expansion factor is designed, and a system covariance matrix is reconstructed for limitation compensation; the method comprises the following steps: constructing chi-square test statistics through an innovation sequence, identifying a system gross error, designing a robust weight function based on a system residual vector, selecting whether to carry out variance correction or not according to an identification result, inhibiting the cumulative influence of a model mismatch error on state estimation, updating a state, and adjusting robust intensity. According to the method, parameter uncertainty robust control and an IREKF algorithm based on innovation detection are introduced to carry out dynamic compensation on a model mismatch error, REKF is improved through innovation detection, and the robust intensity is dynamically adjusted.