Precise torque control for interior mounted permanent magnet synchronous motors with recursive least squares algorithm based parameter estimations

Abstract

Interior mounted permanent magnet (IPM) machines have superior features comparing to their counterparts for electric vehicle traction applications. Having relatively higher efficiency, high torque and power densities, low torque ripple and not requirement of regular maintenance are among their superior features. It is widely known that the precise torque control in practical IPM drives highly relies on accurate knowledge of machine parameters viz, inductance values and magnetic flux linkage. These machine parameters vary significantly in real time operation depending on manufacturing tolerance, operating temperature, inductance saturation, load torque and so on. It is known that d- and q- axis inductances and magnetic flux linkage at the full load operation may be approximately 20%, 35% and 20%, respectively, lower than their actual values at no-load operation. It is also commonly known in the literature for traction applications that these variations (considering wide range operation) have much influence on both drive system efficiency and output torque production compared to other system nonlinearities such as stator resistance variation. It has been achieved in this paper that these parameters are estimated online with fairly high accuracies of each, utilizing recursive least squares (RLS) algorithm. The superiority of the proposed drive achieving considerably higher output torque (∼28,7% of peak torque) is validated through extensive realistic simulations with nonlinear machine model of a 4.1 kW prototype IPM machine designed and manufactured for traction applications. Proposed strategy and its superiority among state-of-art drives are discussed in detail.