Abstract: At least one example embodiment discloses a system including a memory storing instructions and at least one controller configured to execute the instructions to cause the system to obtain a measured speed of an electric machine and a measured position of the electric machine based on output from a sensor, select an observer based on a speed value, obtain an estimated speed of the electric machine and an estimated position of the electric machine using the selected observer, determine a control output based on the measured speed and the measured position, the control output being the measured speed and the measured position or the estimated speed and the estimated position and control the electric machine using the control output.

Abstract: A motor control system includes a motor including a plurality of windings, a first sensor configured to sense a first operating parameter of the motor, a second sensor configured to sense a second operating parameter of the motor, and memory hardware configured to store a machine learning model and computer-executable instructions. The machine learning model is trained to generate a winding temperature estimation output based on motor operating parameter inputs. The motor control system includes processor hardware configured to execute the instructions and use the machine learning model to cause the motor control system to generate a winding temperature estimation output using the machine learning model based on the first operating parameter and the second operating parameter, the temperature estimation output indicative of a predicted temperature of the plurality of windings, and control the motor based on the winding temperature estimation output.

Abstract: A capacitor has a known capacitance value for filtering the ripple current of the DC voltage bus. A first modulation index estimator is configured to estimate a first modulation index of the first inverter. A second modulation index estimator configured to estimate a second modulation index of the second inverter. A current estimator is configured to estimate an interleaving phase shift angle associated with a respective one of a set of inverters based on the known capacitance value of the capacitor, the estimated first modulation index, the estimated second modulation index, the first control input and the second control input.

Abstract: One or more example embodiments provide systems and methods for using impedance separation and impedance shaping.

Abstract: A motor control system includes a motor including a plurality of windings, a first sensor configured to sense a first operating parameter of the motor, a second sensor configured to sense a second operating parameter of the motor, and memory hardware configured to store a machine learning model and computer-executable instructions. The machine learning model is trained to generate a winding temperature estimation output based on motor operating parameter inputs. The motor control system includes processor hardware configured to execute the instructions and use the machine learning model to cause the motor control system to generate a winding temperature estimation output using the machine learning model based on the first operating parameter and the second operating parameter, the temperature estimation output indicative of a predicted temperature of the plurality of windings, and control the motor based on the winding temperature estimation output.

Abstract: A capacitor has a known capacitance value for filtering the ripple current of the DC voltage bus. A first modulation index estimator is configured to estimate a first modulation index of the first inverter. A second modulation index estimator configured to estimate a second modulation index of the second inverter. A current estimator is configured to estimate an interleaving phase shift angle associated with a respective one of a set of inverters based on the known capacitance value of the capacitor, the estimated first modulation index, the estimated second modulation index, the first control input and the second control input.

Abstract: A motor control system includes a motor including a plurality of windings, a first sensor configured to sense a first operating parameter of the motor, a second sensor configured to sense a second operating parameter of the motor, and memory hardware configured to store a machine learning model and computer-executable instructions. The machine learning model is trained to generate a winding temperature estimation output based on motor operating parameter inputs. The motor control system includes processor hardware configured to execute the instructions and use the machine learning model to cause the motor control system to generate a winding temperature estimation output using the machine learning model based on the first operating parameter and the second operating parameter, the temperature estimation output indicative of a predicted temperature of the plurality of windings, and control the motor based on the winding temperature estimation output.

Abstract: A control module comprises software instructions for execution by an electronic data processor. An inductance estimator is configured to estimate direct inductance and quadrature inductance associated with the electric machine based on a first set of equations that assume constant rotor resistance and constant magnetic flux. A torque estimator is configured to estimate an observed torque associated with a rotor of the electric machine based a commanded direct-axis voltage and a commanded quadrature-axis voltage, where the observed torque is proportional to the observed power consumption of the electric machine. A pulse-width-modulation (PWM) module is configured to provide pulse-width modulated signals to the electric machine based on the commanded direct-axis voltage and a commanded quadrature-axis voltage. A back-electromotive force adjustment is derived from an estimated, observed torque and a commanded torque.

Abstract: One or more example embodiments provide systems and methods for using impedance separation and impedance shaping.

Abstract: A control module comprises software instructions for execution by an electronic data processor. An inductance estimator is configured to estimate direct inductance and quadrature inductance associated with the electric machine based on a first set of equations that assume constant rotor resistance and constant magnetic flux. A torque estimator is configured to estimate an observed torque associated with a rotor of the electric machine based a commanded direct-axis voltage and a commanded quadrature-axis voltage, where the observed torque is proportional to the observed power consumption of the electric machine. A pulse-width-modulation (PWM) module is configured to provide pulse-width modulated signals to the electric machine based on the commanded direct-axis voltage and a commanded quadrature-axis voltage. A back-electromotive force adjustment is derived from an estimated, observed torque and a commanded torque.

Abstract: A sensor is configured to sense current, of one or more output phases of an inverter, associated with back electromotive force (back EMF) of the machine. A converter or electronic data processor is adapted to convert the sensed current into current vectors associated with a stationary reference frame. An estimator or current model is configured to estimate back-EMF vectors from the converted current vectors. A vector tracking observer or the electronic data processor is adapted to mix the back-EMF vectors and applying the mixed back-EMF vectors to a preliminary inertial model. A secondary observer or the data processor is operable to apply the output of the preliminary inertial model to a secondary inertial model in the second speed range to estimate position or motion data for the rotor.

Abstract: At least one example embodiment discloses a system including a memory storing instructions and at least one controller configured to execute the instructions to cause the system to obtain a measured speed of an electric machine and a measured position of the electric machine based on output from a sensor, select an observer based on a speed value, obtain an estimated speed of the electric machine and an estimated position of the electric machine using the selected observer, determine a control output based on the measured speed and the measured position, the control output being the measured speed and the measured position or the estimated speed and the estimated position and control the electric machine using the control output.

Abstract: A sensor is configured to sense current, of one or more output phases of an inverter, associated with back electromotive force (back EMF) of the machine. A converter or electronic data processor is adapted to convert the sensed current into current vectors associated with a stationary reference frame. An estimator or current model is configured to estimate back-EMF vectors from the converted current vectors. A vector tracking observer or the electronic data processor is adapted to mix the back-EMF vectors and applying the mixed back-EMF vectors to a preliminary inertial model. A secondary observer or the data processor is operable to apply the output of the preliminary inertial model to a secondary inertial model in the second speed range to estimate position or motion data for the rotor.

Abstract: A method of operating a hybrid electric vehicle includes driving an engine to generate mechanical energy, converting the mechanical energy into a first AC voltage, estimating a total DC link current associated with a respective plurality of loads of the hybrid electric vehicle, converting, with a first inverter, the first AC voltage into a DC bus voltage by regulating the DC bus voltage based on the total DC link current, and inverting, with a respective plurality of inverters, the DC bus voltage into a respective plurality of other AC voltages to drive the respective plurality of loads on the hybrid electric vehicle.

Abstract: A method of operating a hybrid electric vehicle includes driving an engine to generate mechanical energy, converting the mechanical energy into a first AC voltage, estimating a total DC link current associated with a respective plurality of loads of the hybrid electric vehicle, converting, with a first inverter, the first AC voltage into a DC bus voltage by regulating the DC bus voltage based on the total DC link current, and inverting, with a respective plurality of inverters, the DC bus voltage into a respective plurality of other AC voltages to drive the respective plurality of loads on the hybrid electric vehicle.

Abstract: A voltage difference is determined between the observed voltage and a reference direct current bus voltage. A quadrature-axis (q-axis) voltage command is outputted based on a current difference derived from the voltage difference. A commanded direct-axis (d-axis) voltage is determined based on a measured d-axis current and a determined d-axis reference current derived from a mathematical relationship between d-axis residual voltage, the observed voltage and the commanded q-axis voltage, where residual voltage is proportional to a function of the observed voltage and the commanded q-axis voltage. An inverse Parks transformation module or a data processor provides one or more phase voltage command based on inverse Parks transform of the commanded voltages.

Abstract: In one example embodiment, a method includes determining a first adjustment value for a slip frequency of a rotor in an induction motor, determining a second adjustment value for an inductance of the induction motor and tuning the slip frequency of the rotor and the inductance of the induction motor based on the first adjustment value and the second adjustment value, respectively.

Abstract: A capacitor is connected between the direct current voltage terminals. Switched terminals of a first switch and a second switch are coupled in series, between the direct current voltage terminals. An electric machine or generator has one or more windings and a first phase output terminal associated with the switched terminals. A first set of blocking diodes are cascaded in series and second set of blocking diodes are cascaded in series. A first voltage supply provides a first output voltage level and a second output level switchable to the first control terminal, where the first output level is distinct from the second output level. A second voltage supply provides the first output voltage level and the second output level switchable to the second control terminal.

Abstract: A capacitor is connected between the direct current voltage terminals. Switched terminals of a first switch and a second switch are coupled in series, between the direct current voltage terminals. An electric machine or generator has one or more windings and a first phase output terminal associated with the switched terminals. A first set of blocking diodes are cascaded in series and second set of blocking diodes are cascaded in series. A first voltage supply provides a first output voltage level and a second output level switchable to the first control terminal, where the first output level is distinct from the second output level. A second voltage supply provides the first output voltage level and the second output level switchable to the second control terminal.

Abstract: A voltage difference is determined between the observed voltage and a reference direct current bus voltage. A quadrature-axis (q-axis) voltage command is outputted based on a current difference derived from the voltage difference. A commanded direct-axis (d-axis) voltage is determined based on a measured d-axis current and a determined d-axis reference current derived from a mathematical relationship between d-axis residual voltage, the observed voltage and the commanded q-axis voltage, where residual voltage is proportional to a function of the observed voltage and the commanded q-axis voltage. An inverse Parks transformation module or a data processor provides one or more phase voltage command based on inverse Parks transform of the commanded voltages.