Abstract: Reduced computation time for model predictive control (MPC) of a five level dual T-type drive considering the DC link capacitor balancing, the common-mode voltage (CMV) along with torque control of an open-ends induction motor based on determining a reduced set of switching states for the MPC. The reduced set of switching states are determined by considering either CMV reduction (CMVR) or CMV elimination (CMVE). Cost function minimization generates a voltage vector, which is used to produce gating signals for the converter switches. The reduced switching state MPC significantly reduces computation time and improves MPC performance.

Abstract: Capacitor balancing of a dual three-level (3L) T-type converter based on silicon carbide (SiC) discrete semiconductors was performed with the converter feeding an open-ends induction motor (OEIM). A model predictive control (MPC) using a two step cost function calculation was developed to balance the DC link capacitors and control the machine torque simultaneously. The number of redundant switching states used was reduced without affecting the operating voltage vectors, which substantially reduced the computational time. A simulation and experimental results are in good agreement.

Abstract: Reduced computation time for model predictive control (MPC) of a five level dual T-type drive considering the DC link capacitor balancing, the common-mode voltage (CMV) along with torque control of an open-ends induction motor based on determining a reduced set of switching states for the MPC. The reduced set of switching states are determined by considering either CMV reduction (CMVR) or CMV elimination (CMVE). Cost function minimization generates a voltage vector, which is used to produce gating signals for the converter switches. The reduced switching state MPC significantly reduces computation time and improves MPC performance.

Abstract: Capacitor balancing of a dual three-level (3L) T-type converter based on silicon carbide (SiC) discrete semiconductors was performed with the converter feeding an open-ends induction motor (OEIM). A model predictive control (MPC) using a two step cost function calculation was developed to balance the DC link capacitors and control the machine torque simultaneously. The number of redundant switching states used was reduced without affecting the operating voltage vectors, which substantially reduced the computational time. A simulation and experimental results are in good agreement.

Abstract: Reduced computation time for model predictive control (MPC) of a five level dual T-type drive considering the DC link capacitor balancing, the common-mode voltage (CMV) along with torque control of an open-ends induction motor based on determining a reduced set of switching states for the MPC. The reduced set of switching states are determined by considering either CMV reduction (CMVR) or CMV elimination (CMVE). Cost function minimization generates a voltage vector, which is used to produce gating signals for the converter switches. The reduced switching state MPC significantly reduces computation time and improves MPC performance.

Abstract: Reduced computation time for model predictive control (MPC) of a five level dual T-type drive considering the DC link capacitor balancing, the common-mode voltage (CMV) along with torque control of an open-ends induction motor based on determining a reduced set of switching states for the MPC. The reduced set of switching states are determined by considering either CMV reduction (CMVR) or CMV elimination (CMVE). Cost function minimization generates a voltage vector, which is used to produce gating signals for the converter switches. The reduced switching state MPC significantly reduces computation time and improves MPC performance.

Abstract: A method for controlling an electric drive system and the electric drive system. The method includes: measuring an external variable; estimating a control variable for a current sampling step with a mathematical model; predicting a control variable for a future sampling step for each of a plurality of candidate voltage vectors selected for the future sampling step; and calculating a cost function, and identifying a primary voltage vector giving a minimum, where the cost function is defined as a deviation between the predicted stator flux and the reference stator flux. The method further includes: predefining a lookup table giving a correlation between a nonzero voltage vector and a voltage vector group including four candidate voltage vectors, where the plurality of candidate voltage vectors is selected referring the lookup table. The electric drive system includes motor, power converter, and controller, and configured to perform the method.

Abstract: A method for controlling an electric drive system and the electric drive system. The method includes: measuring an external variable; estimating a control variable for a current sampling step with a mathematical model; predicting a control variable for a future sampling step for each of a plurality of candidate voltage vectors selected for the future sampling step; and calculating a cost function, and identifying a primary voltage vector giving a minimum, where the cost function is defined as a deviation between the predicted stator flux and the reference stator flux. The method further includes: predefining a lookup table giving a correlation between a nonzero voltage vector and a voltage vector group including four candidate voltage vectors, where the plurality of candidate voltage vectors is selected referring the lookup table. The electric drive system includes motor, power converter, and controller, and configured to perform the method.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.

Abstract: A system and a method provide a photovoltaic system which regenerates the output characteristics of the photovoltaic at different ambient condition with high precision under all environmental conditions. The photovoltaic system includes a photovoltaic array, a buck/boost converter, a DC link capacitor to connect the buck/booster converter to a load/inverter, an adaptive network-based fuzzy inference maximum power point tracking controller, a voltage control loop, a proportional integral controller to maintain the output voltage of the photovoltaic array to the reference voltage by adjusting the duty ratio of buck/boost converter.