An electric motor system having substantially independent hardware-based and software-based pathways for detecting and initiating responses to fault conditions, such as over-current conditions, in an electric motor which is powered by a power inverter which is controlled by a power module and a microprocessor. Each pathway involves comparing a voltage, which is representative of an electric current flowing to the motor, to a predetermined maximum voltage, and if the former exceeds the latter using hardware or software to initiate shutting off the motor, such as by shutting off the power inverter. When one pathway detects a fault condition it may notify the other pathway, and the notified pathway may also initiate shutting off the motor.

The present invention disclose a method and apparatus for pulse-width modulation (PWM) of a variable-frequency drive (VFD), the method comprising: for each sector of a space vector graph for PWM of the VFD, identifying at least two possible clamping phases in switching between the vectors in the sector; comparing currents in multiple phases in at least one PWM cycle; in the sector of the space vector graph corresponding to the PWM cycle, determining the possible clamping phase with the maximum current in the at least two possible clamping phases; and clamping the determined possible clamping phase with the maximum current.

A method and apparatus for controlling regeneration for a motor. An instantaneous voltage provided by a power supply to the motor is identified using a voltage signal received from a voltage sensor. A new average voltage is computed for the motor using the instantaneous voltage, a previously computed average voltage, and a weight factor for the instantaneous voltage. A difference between the new average voltage and the instantaneous voltage is compared to a selected threshold to determine whether a regeneration condition exists. Operation of the motor is controlled such that a duty cycle of the motor does not decrease in response to a determination that the regeneration condition exists.

Various embodiments include a variable frequency drive motor control apparatus. The apparatus includes a main controller having a first interface. A motor controller is coupled to and controls an electric motor, the motor controller further coupled to the main controller. A network switch is coupled to the main controller, the motor controller, and a remote controller over respective digital connections. The remote controller has a second interface. The network switches data between the first interface, the second interface, and the motor controller. A network coupler is coupled between a variable frequency drive controller and the motor controller.

The present invention provides a computer-readable storage medium which stores a program for causing a computer to generate time-series data of an electric current to be supplied to a motor in order to cause, a control system, including the motor configured to drive an object, to transit from a first state to a second state, the program causing the computer to generate the time-series data so as to satisfy a constraint including a condition to constrain an upper limit value of dispersion of a plurality of state quantities respectively obtained from a plurality of models each of which estimates, from the time-series data, a state quantity of a specific mode of a vibration mode and motion mode of the object, and so that a value of an evaluation function for evaluating the time-series data falls within a tolerance.

An apparatus and method of sensing a motor characteristic signal in a laundry treating appliance having a drum rotated by a motor about a rotational axis, sampling the motor characteristic signal, filtering the motor characteristic signal, and evaluating the filtered motor characteristic signal for the presence of a predetermined condition corresponding to the motor characteristic signal.

A motor control system includes a motor and a motor control circuitry. The motor includes a rotation axis and a bearing rotatably supporting the rotation axis. The motor control circuitry is configured to control the motor. The motor control circuitry includes a driving time adding circuit configured to add up a driving time of the motor to obtain an accumulated driving time of the motor, a remaining lifetime calculation circuit configured to calculate a remaining lifetime of the bearing based on a lifetime of the bearing and the accumulated driving time, and a warning outputting circuit configured to output warning information when the remaining lifetime is equal to or less than a threshold.

An electric power assist device includes a processor including hardware. The processor assists human power input from a user to a drive member with power of a motor, determines whether a current position is located outdoors using a signal from a sensor, and when determination is made that the current position is located outdoors, reduces an assist amount by the motor as compared with a case where the current position is located indoors.

A motor control apparatus (2) according to the present disclosure is configured to control motors (#1-#3), automatically acquire identification information of a plurality of encoders (#1-#5), the encoders (#1-#5) being configured to be connected in series under a control of the motor control apparatus (2) and to detect position information of the motors (#1-#3) or position information of a mechanical apparatus configured to be driven by the motors (#1-#3), and store the identification information and the motor control unit in a non-volatile memory (11) in association with each other.

A computer-implemented method of predicting conditions of machines as well as a corresponding data processing system, computer program and computer-readable medium are disclosed. A technical specification of a machine is received. A data set including at least one current operational parameter of the machine is continuously received. A current load of the machine is continuously derived based on the provided technical specification and the received data set via a knowledge base. A current condition of the machine is continuously predicted by integrating over the derived current load and all previously derived current loads.