Sensorless Adaptive SMO with Mixed Order Generalized Integrator based N-PLL PMSM Drive for LEV Application

The conventional SMO with low pass filter has many limitations due to discontinuous switching function and performance deteriorates at low speed. This paper presents an adaptive sliding mode observer (SMO) based on surface permanent magnet synchronous motor (SPMSM) model for sensorless speed and position estimation. Furthermore, to reduce chattering of the conventional SMO, an improved SMO, which consists continuous sigmoid function with speed based adaptive feedback gain, is presented for estimating back electromotive forces of SPMSM. To extract rotor speed and position, a novel dual mixed order generalized integrator (MOGI) based normalized phase locked loop (NPLL) is utilized. The presented MOGI filter is the combination of second and third order generalized integrator has better capability of harmonics elimination and better DC offset rejection from estimated back-EMF. The comparative analysis of back-EMF, speed and position estimation is presented in this paper. The overall sensorless SPMSM performance is supported by obtained results.

I. Introduction

Discussions in society about the potential for low-carbon or even carbon emission free solutions have been sparked by the imminent concerns of relentless climate change. The transportation sector is one of the largest energy consumption sector, which needs to be fully electrify in the future. Currently, initial cost, motor and controller technology and charging infrastructure are the main challenges for electric vehicles (EVs) [1].