17514results about "AC motor control" patented technology

The present invention provides a permanent magnet motor load adaptive energy-saving optimization method and system based on artificial intelligence, which relates to the field of motor technology, including extracting features and analyzing working conditions of collected real-time motor load data through a deep neural network model to obtain a load feature vector. Then, a reinforcement learning algorithm based on a deep Q network and a policy gradient network is used to output optimal control parameters including excitation current, switching frequency, and power factor according to the load feature vector, and adjust the motor operating state in real time. Finally, the online learning system updates the model and algorithm parameters in real time through a self-correction module according to the comparison results of the operating data and the energy consumption optimization target to achieve closed-loop control. The present invention can adaptively adjust the motor control parameters according to load changes to achieve the purpose of energy-saving optimization.

The invention provides a parameter self-tuning control method for a permanent magnet synchronous motor, and relates to the technical field of synchronous motor control, and the method comprises the steps: firstly, monitoring a dynamic operation data set, including stator current, rotor flux linkage, rotating speed fluctuation quantity and load change characteristic parameters, of the permanent magnet synchronous motor in real time; secondly, feature relevance mapping is carried out based on multiple parameter combinations in the dynamic operation data set, initial parameter adjustment sets are generated, and each initial parameter adjustment combination comprises the mapping relation between the motor operation state and the target response index; dividing a plurality of parameter adjustment subsets according to the parameter correlation degree, configuring a dynamic error range, extracting a positive adjustment parameter from the first subset corresponding to the first operation state, and extracting a negative adjustment parameter from the second subset with the low correlation degree; and finally, training a dynamic parameter adjustment model by utilizing the positive adjustment parameters and the negative adjustment parameters, generating an optimized real-time parameter setting instruction set, realizing intelligent self-setting of the parameters of the permanent magnet synchronous motor, and improving the running performance of the motor.

The invention belongs to the technical field of motor control, and discloses a control method of a motor for an inverter compressor, which comprises the following steps: embedding a distributed thermocouple array in a motor stator slot to acquire temperature data of the motor, synchronously acquiring operation parameters of the motor, generating a dynamic thermal field characteristic spectrum through a data fusion algorithm, coordinates of the hot spot areas with the temperature abnormally increased are marked, a dynamic correlation model is established, and heat conduction characteristic parameters in the dynamic correlation model are updated through a sliding window algorithm; outputting a predicted temperature rise curve through the dynamic correlation model, adjusting a PWM control strategy of the inverter, inputting the PWM control strategy to a motor driving unit to execute preliminary regulation and control, collecting feedback data to generate a multi-dimensional feedback feature vector, iteratively optimizing a combined weight of a switch interval compensation amount and a harmonic injection strategy through a gradient descent algorithm, and performing harmonic injection control. And a global optimal strategy considering the heat dissipation efficiency and the operation stability is formed, and the operation stability and the energy efficiency level of the inverter compressor under various working conditions are remarkably improved.

The invention provides an artificial intelligence-based permanent magnet motor energy efficiency optimization and energy-saving control method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting motor operation data through employing a multi-dimensional sensor array, carrying out the feature extraction based on a mutual information entropy criterion, constructing a multi-physics field coupling model, and building a digital twinborn model; a double-layer deep reinforcement learning neural network is constructed based on the model, a global optimization target is generated through a high-layer strategy network, and a low-layer execution network adopts a deep deterministic strategy gradient algorithm to decompose sub-targets; training the network by adopting a priority experience playback mechanism to obtain an optimal control strategy; and inputting the optimized parameters into a vector controller to realize three-closed-loop control. The operation efficiency of the permanent magnet motor is improved, and the system stability and the dynamic response performance are enhanced.

The invention relates to the technical field of motor control, in particular to a variable frequency motor dynamic adaptive control method and system based on multi-parameter analysis. The method comprises the following steps: collecting a multi-dimensional electrical operation monitoring parameter flow of a variable frequency motor, carrying out multi-parameter nonlinear correlation analysis and parameter topological correlation reconstruction, and constructing a multi-dimensional feature topological correlation network; a variable frequency motor multi-working-condition travel history database is obtained, multi-working-condition disturbance transient response analysis is carried out, multi-modal behavior prediction evolution is carried out based on the multi-dimensional feature topological association network, and a dynamic multi-modal behavior prediction engine is constructed; and acquiring multi-part electromagnetic sensing parameters of the motor, and performing abnormal electromagnetic intensity fluctuation detection and abnormal part power loss calculation to obtain abnormal part power loss characteristics. The self-adaptive real-time parameter motor control is realized, the energy efficiency of the motor is improved, the maintenance frequency and cost are reduced, and the full-life-cycle optimal control of the motor is realized.

The invention provides a servo motor real-time adaptive control method and system based on artificial intelligence, and the method comprises the steps: injecting a tiny excitation signal into a servo motor, collecting temperature and electromagnetic response data under different working conditions, and constructing a multi-dimensional information data set; performing real-time reasoning on the relationship between the temperature gradient and the magnetic path characteristics by using deep transfer learning to obtain multi-dimensional parameter deviation vectors such as stator flux linkage unbalance degree, permanent magnet flux weakening degree and torque coefficient change; generating a multi-scale compensation strategy through a physical enhancement reinforcement learning method and the multi-dimensional parameter deviation vector; and carrying out Lie group transformation processing on the control law under a differential geometric framework, and realizing accurate compensation on the temperature gradient effect through a dual-channel-dual-time scale framework. According to the method, heterogeneous sensing and multi-dimensional compensation strategies are adopted, the problem that the control precision of a traditional method is insufficient under the complex temperature gradient condition is solved, and the high-precision motion control performance is maintained under the dynamic working condition that the temperature distribution of the motor is rapidly changed.

The invention relates to the technical field of single-phase asynchronous motors, and discloses an electronic soft start control method for a single-phase asynchronous motor, which accurately controls the start process of the motor by combining an MCU (Microprogrammed Control Unit) with an electricity metering chip and a silicon controlled rectifier technology. After the system is powered on, the MCU control unit firstly carries out initialization and reads initial circuit parameters collected by the electricity metering chip, and whether starting conditions are met or not is judged based on the parameters. Once the starting condition is confirmed to be met, the MCU sequentially triggers the auxiliary silicon controlled rectifiers to switch on the starting winding and then triggers the main silicon controlled rectifiers to switch on the main winding, so that the motor enters a running state. As the motor reaches a stable operation state, the MCU control unit closes the auxiliary silicon controlled rectifier to reduce unnecessary energy consumption, and adaptively adjusts the conduction time of the starting winding according to the actual load condition, thereby ensuring that the whole starting process is stable and efficient.

An electrified vehicle may include: a main battery and an auxiliary battery; a motor system including a dual inverter connected to the main battery and driving a motor depending on a motor driving mode, and a transfer switch for switching between first and second driving modes included in the motor driving mode; and a charging switch connected between the motor system and the auxiliary battery, and configured to form a boost charging path connected from the auxiliary battery to the main battery through the motor system when the first driving mode switches to a charging mode while driving.

An in-vehicle charging device that includes a first circuit configured to include the excitation circuit and convert power between AC power on an external AC power supply side and first DC power; and a second circuit configured to include the inverter, the multi-phase stator coils, and an output capacitor, and generate second DC power for charging the DC power supply from the first DC power, wherein the output capacitor is connected between the neutral point of the multi-phase stator coils and a DC negative electrode.

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 relates to the technical field of motor control, and discloses a hybrid excitation synchronous motor control strategy optimization method and device. The method comprises the following steps: performing mathematical modeling on permanent magnet flux linkage, exciting current and rotor parameters of the hybrid excitation synchronous motor to obtain a state observer equation; collecting current parameters and position parameters, and performing filtering processing to obtain motor operation state parameters; inputting a five-layer deep neural network for current and rotating speed parameter prediction to obtain an optimal current parameter and an optimal rotating speed prediction parameter; constructing a multi-objective function, and solving to obtain a current reference value; inputting the current reference value into a cascade PI controller, and performing voltage regulation through feedforward decoupling control and a space vector pulse width modulation technology to obtain a control voltage signal; and performing performance calculation control parameter optimization on the control voltage signal to obtain a target control parameter, thereby improving the control precision of the hybrid excitation synchronous motor.

The present disclosure relates to the technical field of vehicles, and provides a vehicle and an energy conversion device and a control method therefor. The energy conversion device includes a motor controller, a bus capacitor, a first switch module, a motor, and a second switch module. By controlling the first switch module and the second switch module to be turned on / off, a motor driving circuit can be formed by a battery pack, the first switch module, the bus capacitor, the motor controller, and the motor, and a charging and discharging circuit can be formed by the battery pack, the second switch module, the motor, the motor controller, and the bus capacitor.

The invention discloses a three-phase permanent magnet synchronous motor full-speed-domain driving control system and a control method thereof. The system is composed of a torque limiting module, a full-speed-domain control neural network module, a current control module, a coordinate transformation module-I, a coordinate transformation module-II, a coordinate inverse transformation module, an SVPWM module, a SiC MOSFET driving module, a full-speed-domain position rotating speed observation module, a weak magnetic feedback module and a three-phase permanent magnet synchronous motor. The control method is used for driving the control system. According to the method, accurate tracing of the optimal dq-axis reference current working point is realized based on deep learning, and accurate control of three operation modes of MTPA, field weakening control and MTPV is realized; an improved mobile vision field estimation algorithm is adopted, and the rotor position and the rotor rotating speed are accurately estimated within the full-speed domain range; the SiC MOSFET is used as an inverter switching tube, and a brand new drive circuit is designed to adapt to the operation condition of the electric vehicle.

An electrical propulsion system for a vertical take-off and landing (VTOL) aircraft comprises an electrical motor assembly and an inverter assembly. The inverter assembly comprises a housing, a capacitor assembly, at least one printed circuit board assembly (PCBA), and a plurality of positioning pins. The capacitor assembly comprises a center hole, at least one capacitor, a capacitor housing having at least one busbar, and a plurality of through holes in the capacitor housing. The capacitor assembly and the at least one PCBA are positioned inside the housing. The plurality of positioning pins pass through the through the plurality of through holes of the capacitor housing and the at least one PCBA and are connected to the housing.

A control device (100) for controlling an actuator (200) for actuating an optical element (310) of an optical system (4, 10), with an amplifier (110) which is configured to receive a supplied supply voltage (V1) at an input node (K1) and to provide a drive voltage (V2) for the actuator (200) at an output node (K2), and a supply device (120) coupled to the input node (K1) for providing the supply voltage (V1), which has a series connection (130) of a plurality N, with N ≥ 2, of DC / DC converters (131-133) for providing a respective DC voltage and a number M, with M ≥ 1, of further DC / DC converters (141) that can be connected in series to the series connection (130) for providing a DC voltage.

Embodiments include an electric vehicle having a charging port configured to receive an alternating current (AC) power, a direct current (DC) battery, and a bidirectional inverter configured to convert AC power to DC power and to convert DC power to AC power, the bidirectional inverter is selectively connected to the DC battery by propulsion switches. The electric vehicle also includes an AC motor connected to the bidirectional inverter and selectively connected to the charging port by a first charging switch, an isolated DC / DC converter motor selectively connected to the DC battery via a second charging switch and a third charging switch, and a processor configured to control the operation of the propulsion switches, the first charging switch, the second charging switch, and the third charging switch based on an operational mode of the electric vehicle.

The invention belongs to the technical field of motor control, and relates to a permanent magnet synchronous motor sensorless control method, system and hardware circuit, angular velocity estimation is designed based on a q-axis current model under a two-phase rotating coordinate system, angular velocity estimation compensation is designed based on a d-axis current model, and a rotating speed correction coefficient is introduced. And dynamic compensation of the estimated angular velocity value is realized. An accurate angular velocity estimated value and an accurate rotor angle estimated value are obtained by constructing a Romberg observer with an angular velocity estimated value and a rotor angle estimated value as outputs based on a dq rotating coordinate system. Taking an angular velocity error obtained by a motor angular velocity given value and a motor angular velocity estimated value as input of an outer ring PI controller, so as to ensure that the angular velocity estimated value tracks the motor angular velocity given value and output a q-axis current reference value; taking the difference value between the q-axis current reference value and the q-axis current sampling value and the difference value between the d-axis current reference value and the d-axis current sampling value as the input of an inner ring PI controller so as to ensure the bandwidth and the influence capability on the load, and outputting a d-axis voltage reference value and a q-axis voltage reference value; and converting the d-axis voltage reference value and the q-axis voltage reference value into voltage reference values under a two-phase static coordinate system based on the rotor angle estimation value so as to divide SVPWM drive circuit sectors, select voltage vectors, calculate action time, control on and off time of a permanent magnet synchronous motor switching device, and control on-off time of the permanent magnet synchronous motor switching device. And the alternating current speed regulation performance of the permanent magnet synchronous motor without the position sensor under the Romberg observer method is ensured.

The invention provides an elevator energy-saving device which is connected to an elevator frequency converter bus in parallel and comprises a battery pack, a BMS battery management system, a power control system, a DC-DC direct-current power source and a PLC, the DC-DC direct-current power source is connected with the BMS battery management system and connected to the elevator frequency converter bus in parallel, and the power control system is connected with the PLC. The PLC is connected with the DC-DC direct-current power supply, and the DC-DC direct-current power supply transforms the voltage accessed from the battery pack to the second preset voltage under the action of the PLC, so that the voltage of the high-voltage end is controlled to be the second preset voltage; under the action of the high-low voltage difference, when the elevator generates power, the voltage on the elevator frequency converter bus does not rise to the first preset voltage, and the current automatically flows to the elevator energy-saving device. The invention has the characteristics of energy conservation, high efficiency, reduced operation cost, stable operation, reduced power grid pressure and prolonged service life of equipment.

The invention relates to the technical field of vibration and noise control, discloses a new energy automobile motor high-frequency vibration and noise active suppression system and method, and aims to solve the problems of poor high-frequency vibration and noise suppression effect, real-time performance, adaptive capacity and system cost complexity of an existing new energy automobile motor. The method comprises the following steps: acquiring and preprocessing motor operation state data, extracting high-frequency harmonic characteristics, and generating predicted harmonic characteristics in combination with working condition prediction; and superposing the self-adaptive compensation quantity to a motor voltage instruction, and driving an inverter through pulse width modulation to realize active suppression of high-frequency vibration and noise. The system comprises a data acquisition preprocessing module, a harmonic feature extraction module, a working condition sensing prediction module, a self-adaptive compensation quantity generation module and a pulse width modulation correction module. By the adoption of the technical scheme, efficient, real-time and self-adaptive suppression of high-frequency vibration and noise of the motor can be achieved, the level of the high-frequency vibration and noise is remarkably reduced, the driving comfort is improved, and the complexity and cost of the system are optimized.

The invention discloses a high-precision linear vibration feedback motor system, and relates to the technical field of precise electromagnetic driving, and the system comprises a core driving module which is a moving magnet type linear motor of a Halbach array magnetic circuit structure, and is integrated with a multi-physics field sensing unit; the dynamic parameter tracking module is used for acquiring a reed rigidity coefficient, a damping coefficient and a magnetic constant in real time when the motor runs, and establishing a dynamic displacement model based on a recursive least square method; a double-closed-loop control framework is adopted, an inner loop adopts field-oriented control, and an outer loop is based on model prediction control; the aging prediction unit activates a temperature rise compensation algorithm when the accumulated number of vibration times is greater than a set threshold value; the self-adaptive calibration engine is used for injecting a sweep frequency excitation signal when the system is started, and automatically compensating individual difference parameters according to the harmonic peak offset; and the digital twin mapping unit is used for establishing a real-time mapping relationship between the physical parameters of the motor and the virtual model, and dynamically correcting the model parameters by comparing the actual displacement with the model displacement.

The invention relates to a PINN-based permanent magnet synchronous motor parameter identification method. The invention relates to the technical field of permanent magnet synchronous motor driving control, and the method comprises the steps: collecting motor operation parameters, and obtaining the quadrature-direct axis voltage, current and electrical angular velocity of a motor; a PMSM model is built; a PINN model is built; and performing finite element simulation according to the established model to obtain motor operation data, and identifying motor parameters. Compared with a traditional permanent magnet synchronous motor model, the method is higher in precision, and solves the problems that the control performance of the motor is reduced, the dynamic response is not accurate and the efficiency is low due to the influence of a traditional motor equation under a high-load or complex working condition, so as to guarantee the efficient and stable operation of the motor.

The invention belongs to the technical field of permanent magnet synchronous motor position-sensorless control, and discloses a surface-mounted permanent magnet synchronous motor full-speed-domain position-sensorless control method and system. In a zero-low-speed area, a high-frequency square wave voltage injection method is adopted for motor rotor position identification, a simplified signal processing mode is adopted, use of a filter is omitted, and position estimation precision is improved; the improved sliding mode observer is adopted to identify the position of the motor rotor in a medium-high speed domain, and aiming at the problems of buffeting and phase delay of a traditional sliding mode observer, a piecewise square change switching function is adopted to replace a sign function to reduce system buffeting, and a synchronous reference system filter is adopted to replace a low-pass filter to reduce system buffeting. The problems of phase delay and amplitude attenuation caused by back electromotive force are avoided; and an improved weighted switching method with continuous and smooth proportionality coefficients is adopted in a switching speed domain to realize stable switching of the rotating speed. The method has the advantages of being capable of accurately estimating the motor rotating speed and the rotor position in the full-speed domain, fast in dynamic response and good in estimation precision.

An in-vehicle charging device charges a vehicle driving device DC power supply including: a rotating electrical machine including coils of multiple phases connected at a neutral point, and serving as a driving power source of a wheel; an inverter converting power between direct and alternating currents of multiple phases; and the DC power supply connected to the inverter, the in-vehicle charging device including: an AC-DC converter converts power between AC power and first DC power; an active decoupling circuit that includes the inverter, the coils of multiple phases, and an output capacitor, and generates second DC power for charging the DC power supply from the first DC power, in which a DC side terminal of the AC-DC converter and a DC side terminal of the inverter are connected without another passive component, and the output capacitor is connected between the neutral point of the coils and a DC negative electrode.

A system for an electrified vehicle, such as a battery electric vehicle (BEV), includes an inverter configured to drive a motor having motor windings with electrical power from a battery according to a configuration of a power switch of the inverter. The system further includes a capacitor connected between a center-tap of the battery and a neutral-point of the motor winding whereby the capacitor and the motor windings form an LC circuit. The system further includes a controller configured to operate the power switch in a zero-current-switching mode with a switching frequency dependent on a resonant frequency of the LC circuit to thereby cause electrical current to circulate between the battery, the inverter, and the motor which heats the battery and the motor windings.

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.

A monolithic half-bridge gate driver includes a phase node terminal configured to be coupled to a phase node to which a high-side transistor and a low-side transistor of a half-bridge are coupled; a diode comprising an anode and a cathode, wherein the cathode is coupled to the phase node terminal; and a comparator comprising a first input terminal coupled to the anode of the diode for receiving a measurement value indicative of a phase voltage at the phase node terminal, a second input terminal coupled to a threshold source for receiving a threshold, and an output terminal configured to output a comparison result indicating whether the measurement value satisfies the threshold. The phase node terminal is configured to be connected to a high-side supply potential by the high-side transistor, and is configured to be connected to a low-side supply potential by the low-side transistor.

The present teaching relates to method and system for charging a rechargeable battery deployed in an electric apparatus. The system resides in the electric apparatus. The system comprises a motor, an inverter, an output rectifier, a configurator, and a controller. The motor comprises a stator having a plurality of stator teeth and a plurality of stator windings wounded on the plurality of stator teeth. The inverter comprises a plurality of power switch devices. The configurator comprises a plurality of contactors coupled with the plurality of stator windings and the plurality of power switch devices. The controller controls the plurality of power switch devices and the plurality of contactors, so as to configure the system to operate in one of a traction mode and a charging mode.

A motor controller for pulse heating of a power battery. The motor controller includes an inverter circuit, the inverter circuit includes three switching transistor bridge arms, two ends of each switching transistor bridge arm are respectively configured to connect to positive and negative electrodes of the power battery through a direct current bus, and bridge arm midpoints of the three switching transistor bridge arms are separately configured to connect to a three-phase winding of a motor. The bridge arm midpoints of the three switching transistor bridge arms are configured to output a three-phase current, the three-phase current is used to generate a pulse alternating current on the direct current bus, and the pulse alternating current is used to heat the power battery. A current of each phase of the three-phase current is a unipolar triangular wave, and a sum of the three-phase current is zero.

The invention discloses a wide-speed-domain position-sensorless control method for a permanent magnet synchronous motor, and the method comprises the steps: building an extended state observer of the permanent magnet synchronous motor, and obtaining the counter electromotive force of the motor through the extended state observer; a self-adaptive vector filter is adopted to filter out higher harmonics in the back electromotive force obtained by the extended state observer, estimated back electromotive force is obtained, the obtained estimated back electromotive force serves as input, position information contained in the estimated back electromotive force is demodulated through a phase-locked loop position observer, and the rotating speed and the position angle of the motor are obtained; and controlling the permanent magnet synchronous motor according to the obtained rotating speed and position angle. The position observer is used for extracting position information from the rotor back electromotive force, a mechanical position sensor is omitted, the system structure is simplified, cost is reduced, the self-adaptive vector filter is used for filtering harmonic waves for estimating the back electromotive force, and estimation errors of the rotating speed and the position angle of the motor are reduced. And the high efficiency and the stability of position-sensorless control of the motor in a wide speed range are improved.

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.