A powertrain system may determine a power distribution for one or more power sources of a vehicle. The powertrain system may be coupled to a perception system that may provide perception data indicating a scenario, situation, or environment that has been encountered by the vehicle. The powertrain system may include machine learning model that may generate the power distribution based on one or more of the perception data and a power request.

A power conversion apparatus includes a main circuit unit, a control unit, a current sensor, and a half-wave rectifier unit. The control unit includes current frequency calculation units and monitoring units. The current frequency calculation units calculate current frequencies based on at least either the rising timing or falling timing of current detection signals half-wave rectified by the half-wave rectifier unit. The monitoring units monitor the speed of a motor based on the current frequencies calculated by the current frequency calculation units.

A motor control method inputs one or more controlled variables or target values each representing a state of a motor to one or more node layers as an input value, and performs calculation in each of the one or more node layers to output one or more manipulated variables used for control of the motor and control the motor in accordance with the one or more manipulated variables. Each the one or more node layers has a plurality of nodes that execute calculations in parallel. Each of the plurality of nodes multiplies the input value by a coefficient specified for the corresponding node, and performs calculation using a function specified for the corresponding node and designating a multiplied value as an input variable to determine an output value.

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.

An apparatus for driving a motor comprising a first plurality of neurons of neural network circuitry, motor circuitry, and a second plurality of neurons of the neural network circuitry. The first plurality of neurons is configured to generate a first cycle value based on a target speed. The motor circuitry is configured to control, based on the first cycle value, a set of switching elements to drive the motor. The second plurality of neurons is configured to train the second plurality of neurons to generate, based on a resulting speed value for the motor that occurs when the motor circuitry has controlled the set of switching elements to drive the motor based on the first cycle value, a second cycle value to minimize a difference between the second cycle value and the first cycle value.

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.

A system in a vehicle includes a controller to implement a neural network to provide current commands based on inputs. The inputs include a torque input. The system also includes a current controller to provide a three-phase voltage through an inverter based on the current commands from the controller. An electric traction motor provides drive power to a transmission of the vehicle based on injection of the three-phase voltage. The current commands resulting from implementation of the neural network are corrected based on estimated torque resulting from the injection of the three-phase voltage to the electric traction motor.

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 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.

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.