Sensor-less Speed Estimation using Improved Stator Current Model Reference Adaptive System for Induction Motor

The electric motor plays a vital role as the primary component in an electric vehicle (EV) drivetrain. Selecting the right control algorithm is crucial in order to achieve the desired speed and torque characteristics. In both the industrial and automotive sectors, there is a growing preference for sensor-less speed estimation techniques due to their compact design. It eliminates use of encoders, decoders, position and speed sensor in system. The paper proposes the improved stator current model reference adaptive system (MRAS) with field oriented control (FOC) for induction motor (IM) drive. The proposed technique is seen to be more effective than other sensor-less control techniques as it reduces the computational burden, noise, chattering and instability issue in regenerative operation. The improved stator current model reference adaptive system (MRAS) performance is evaluated using MATLAB Simulink in various scenarios, including steady-state conditions, transient conditions, and speed reversals. The performance of proposed technique is validated with conventional stator current MRAS at different speed condition. The result analysis ensures that reduction in settling time, overshoot, better speed tracking and accuracy.