Performance improvement of sensorless scalar and vector control for induction motor drives via an enhanced voltage model

Introduction. Scalar control (SC) and field-oriented control (FOC) are widely used in sensorless induction motor (IM) drives for their balance of performance and cost. Among estimation techniques, the voltage-model (VM) based model reference adaptive system (MRAS) is preferred in industry due to its simple structure and low computational load. Problem. Traditional VM-based MRAS schemes are highly sensitive to parameter uncertainties, especially to variations in stator resistance Rs caused by temperature changes. These variations degrade flux estimation accuracy, leading to significant speed-tracking errors, increased transients, and reduced stability in both SC and FOC. Goal. This study quantitatively evaluates how the estimation of stator resistance Rs and the dependent rotor resistance Rr affects the speed-control performance of sensorless SC and FOC under parameter mismatch. Methodology. An improved VM-based MRAS is proposed with parallel Rs estimation and Rr updated via a linear relation to Rs. Estimator stability and convergence are proven using Lyapunov theory. The estimator is integrated into SC and FOC and tested in MATLAB/Simulink under identical conditions, including a sudden 30 % increase in resistance. Speed tracking is quantified using the integral of time-weighted absolute error (ITAE). Results. Parameter estimation markedly enhances the robustness of both strategies. In sensorless SC, ITAE drops by about 66.2 % (5.512 to 1.863), indicating much lower transient oscillations. In sensorless FOC, ITAE falls by about 54 % (0.7075 to 0.323), with speed overshoot nearly eliminated (0.031). Scientific novelty. The study provides a unified quantitative comparison of sensorless SC and FOC using ITAE under identical operating and estimation conditions, revealing different levels of performance recovery with the proposed dual-resistance adaptation. Practical value. The findings guide the design of more reliable industrial IM drives, showing that while FOC retains superior dynamics, SC with estimation becomes a robust, cost-effective option for applications with significant parameter uncertainty. References 31, table 1, figures 13.