Dynamic output feedback linearizing control of saturated induction motors with torque per Ampere ratio maximization

Dynamic output feedback linearizing control of saturated induction motors with torque per Ampere ratio maximization

Dynamic output feedback linearizing control of saturated induction motors with torque per Ampere ratio maximization, 2016 2nd International Conference on Intelligent Energy and Power Systems (IEPS), Kiev
S. Peresada, S. Kovbasa, S. Dymko and S. Bozhko

The paper presents a novel maximum torque per Ampere (MTA) controller for induction motor (IM) drives. The proposed controller exploits the concept of direct (observer based) field orientation and guarantees asymptotic torque tracking of smooth reference trajectories and maximizes the torque per Ampere ratio when the developed torque is constant or slowly varying. A dynamic output-feedback linearizing technique is employed for the torque subsystem design. In order to improve torque tracking accuracy a motor magnetizing curve is taken into account during MTA optimization and controller design. The achieved steady-state system efficiency have been compared experimentally for three types of controllers, namely: standard vector control with constant flux operation, controller based on classic maximization of torque per Ampere ratio for linear magnetic circuit and controller based on MTA strategy for saturated induction motor. It is shown experimentally that the controller designed for saturated induction motor provides not only higher torque per Ampere ratio but also increases power factor and reduces active power consumption hence improving the drive efficiency. Operation with slowly varying torque references has also been analysed. It is shown that the proposed controller is suitable for applications that do not demand an extremely fast dynamic response, for example for electric vehicle drives.

S. Peresada, S. Kovbasa, S. Dymko and S. Bozhko, “Dynamic output feedback linearizing control of saturated induction motors with torque per Ampere ratio maximization,” 2016 2nd International Conference on Intelligent Energy and Power Systems (IEPS), Kiev, 2016, pp. 181-186.