Q-MRAC Based Online Rotor Resistance Estimation Technique Considering the Saturated Magnetizing Inductance of an Indirect Rotor Flux Oriented Vector Controlled Induction Motor Drive for an Electric Vehicle

This paper proposes a Reactive power-based Model Reference Adaptive Controller (Q-MRAC) for the real-time estimation of rotor resistance considering the magnetizing inductance saturation, for an IFOC based induction motor drive used in electric vehicle (EV). The online estimated rotor resistance is updated in the IFOC operation by carefully observing the dynamics of the EV. In general, EVs operate in the flux saturation region to achieve higher gradients as well as the compactness of the overall drive system. The saturated flux operation of an induction motor has a variable magnetizing inductance profile depending on the level of saturation. The proposed Q-MRAC considers the complete magnetizing inductance variation profile to estimate an accurate value of rotor resistance, and updates into the IFOC algorithm without affecting the vehicle dynamics. The proposed controller makes the EV drive system more efficient. This estimation works accurately at all magnetization levels and stator frequencies. The simulation results validate the effectiveness of the proposed estimation technique.