Stator Flux Estimation Based on a Kalman Filter for Stator Flux Vector Control of a Doubly-Fed Induction Motor

Abstract

Reliable knowledge of the stator flux vector is essential for stator flux vector control of a doubly-fed induction motor (DFIM); therefore, reliable flux estimation is required. Several flux observers have been proposed while the Kalman filter is well known as an optimal state estimator for linear systems. In this paper, a Kalman-filter-based stator flux observer is developed and combined with a double second-order generalized integrator phase-locked loop (DSOGI-PLL) to estimate the flux angular speed and position under non-ideal grid conditions. This work is validated through computer simulation in PLECS software. The CMSIS-DSP library is adopted to perform matrix operations of the Kalman filter. Simulations were performed under different operating conditions, demonstrating that the proposed approach successfully estimates the stator flux vector of the DFIM.