Accurate adaptive integration algorithms for induction machine drive over a wide speed range

Abstract

This paper presents three new architectures for designing accurate adaptive integration algorithms (AAIA) for quasi exact flux position and magnitude estimation of induction machines over a wide speed range. Pure integrators are in practice affected by DC-offset and DC-drift problems while estimating flux position and magnitude from the back electromotive force (emf). Modified integration algorithms based on low pass filter (LPF) or programmable LPF are also known to be affected by the cut-off frequency. The proposed architectures are based on the association of high pass filters (HPF) and pure integrators. DC-offsets and drift problems are eliminated by the HPFs before integration. The HPF characteristics are used for magnitude (gain) and position (angle) compensation. The HPF cut-off frequency can be chosen far from the inverse of stator time constant without affecting the estimation of low frequency signals resulting into good accuracy over a wide speed range. A strong agreement is observed between the simulation and experimental results that demonstrate the accuracy of the proposed architectures. The proposed AAIA can be used for any kind of induction machine (IM) since they are independent from the IM parameters. The AAIA can also be used to estimate stator flux in order to estimate the IM parameters online, as required for adaptive control in indirect rotor flux oriented control (IRFOC) schemes