An adaptive system and a method for adjusting a parameter in the adaptive system includes operating an adaptive system with an output signal produced from an input signal applied to an input, in which a parameter with a finite range is determined based on a difference between the output signal and a target output signal. In one example the parameter with the finite range is a fixed-point parameter or an analog parameter. The parameter is accessed from the adaptive system. A probability distribution of the parameter is assigned. The finite range for the parameter is updated based on the probability distribution which has been assigned. The probability distribution function may be updated alone with the finite range of the parameter. The probability distribution may be derived from one or more historical values of the parameter, and a plurality of system parameters belonging to an identical category of data as the parameter.

In a motor drive control device including a machine learning function, appropriate motor drive control in accordance with the usage environment of a motor is realized. A motor drive control device 10 includes: a measurement data generation unit 23 that generates measurement data 300 relating to operation of a motor 50; a training data generation unit 24 that attaches predetermined identification information indicating the operation state of the motor 50 to the measurement data 300 and generates training data 310; a machine learning unit 25 that generates a learned model 320 for determining the operation state of the motor 50 by performing machine learning using the training data 310; and a monitor control unit 26 that monitors the operation state of the motor 50 using the learned model 320. In the motor drive control device 10, the training data generation unit 24 starts generation of the training data 310 when the training data generation unit 24 receives a command ordering acquisition of the training data 310 from a host device 4.

A motor monitoring system includes a motor unit, a plurality of sensors, and a motor controller. The motor unit includes a motor housing and a motor arranged within the motor housing. The motor includes a stator with a plurality of stator poles each having a corresponding phase coil. The plurality of sensors are arranged within the motor housing and are configured to: measure a first characteristic related to partial discharges that occur at one or more phase coils, and generate sensor data based on the measured first characteristic. The motor controller is configured to generate a plurality of pulse width modulation (PWM) control signals for controlling phase voltages of the motor, detect the partial discharges at at least one of the phase coils based on the sensor data, and adjust at least one PWM control signal of the plurality of PWM control signals based on the detected partial discharges.

A method for adaptive motor control includes acquiring current parameters in an operation process of the motor at a current moment; determining a type of a region in which the motor operates at the current moment according to the current parameters; triggering a corresponding motor model according to the type of the region in which the motor operates at the current moment; and inputting the current parameters into the corresponding motor model, generating control parameters for motor operation according to the current parameters, and controlling the operation of the motor according to the control parameters for motor operation. An apparatus and a computer-readable storage medium are also disclosed. In comparison with the conventional motor control which uses the single nonlinear model, the motor control method disclosed herein can greatly improve the reliability of the control.

A system for reducing at least one of motor loss or motor drive loss in a vehicle. The system includes a motor designed to convert electrical energy into torque. The system also includes a sensor designed to detect motor data corresponding to at least one of a motor torque or a motor speed of the motor. The system also includes a memory designed to store testing data including optimized current commands for multiple combinations of motor torques that were determined during testing of the motor or a similar motor. The system also includes a speed or torque controller coupled to the motor, the sensor, and the memory and designed to receive a speed or torque command and to determine a current command signal usable to control the motor based on the speed or torque command, the testing data, the detected motor data, and an artificial intelligence algorithm.

A control system for controlling a power generator of a power generation system executes a control policy to map an input-and-output sequence to a current value of the excitation voltage, submits the current value of the excitation voltage to the power generator, accepts a current value of the rotor angle caused by actuating the power generator according to the current value of the excitation voltage, and updates the input-and-output sequence with the corresponding current values of the rotor angle and the excitation voltage. The input-and-output sequence of values of the operation of the power generator includes a sequence of multiple values of the rotor angle of the power generator and a corresponding sequence of multiple values of excitation voltage to the power generator causing the values of the rotor angle. The control policy maps the input-and-output sequence to a current control input defining the current value of the excitation voltage.

An abnormality determination system includes a state quantity obtaining circuit and an abnormality determination circuit. The state quantity obtaining circuit is configured to obtain a state quantity associated with a mechanical system. The abnormality determination circuit is configured to, according to a learning content obtained in a machine learning process and based on the state quantity, determine as to at least one of an occurrence of an abnormality in the mechanical system, an occurrence position of the abnormality, and a cause of the abnormality.

The present invention pertains to methods for operation, maintenance, and monitoring of rotating electrical machines, and relates to a system and a method for monitoring the operational condition and detecting mechanical, electrical, load, and process faults in rotating electrical machines. The proposed system and method, together, provide a more effective way to detect faults early on, with greater installation convenience and scalability than prior art methods, and are more efficient in avoiding production losses, improving operational performance and preventing damage to equipment and risks to operators. The developed method continuously collects electrical current and voltage signals that power the machine, utilizing a data acquisition module and current and voltage transformers. The collected data undergoes stages of compression, encryption, application of Fast Fourier Transform (FFT), subsampling, feature extraction, anomaly detection using statistical and machine learning techniques, and fault classification using machine learning techniques. The proposed system consists of one or more data acquisition modules, one or more gateway devices, a processing center on a cloud computing platform, and an operator interface. In an industrial application, the method can be continually improved with the collection of new data and with validation information from an operator in the face of an identified fault.

Systems and methods of controlling a length of an air gap in an electric machine using an air gap controller may include: determining an air gap length value for an electric machine at least in part using an air gap controller, comparing the determined air gap length value to an air gap target value using the air gap controller, and outputting a control command from the air gap controller to a controllable device associated with an air gap control system when the determined air gap length value differs from the air gap target value by a predefined threshold. A control command may be configured to impart a change to an operating parameter associated with the air gap control system to adjust a length of an air gap between an outer surface of a rotor core and an inner surface of a stator core of the electric machine.

A system for reducing at least one of motor loss or motor drive loss in a vehicle. The system includes a motor designed to convert electrical energy into torque. The system also includes a sensor designed to detect motor data corresponding to at least one of a motor torque or a motor speed of the motor. The system also includes a memory designed to store testing data including optimized current commands for multiple combinations of motor torques that were determined during testing of the motor or a similar motor. The system also includes a speed or torque controller coupled to the motor, the sensor, and the memory and designed to receive a speed or torque command and to determine a current command signal usable to control the motor based on the speed or torque command, the testing data, the detected motor data, and an artificial intelligence algorithm.