Events

Improvised model predictive control methods for dual inverter fed open end winding induction motor drive

  • 01

    Dec

    2022


Name of the Speaker: Naga Surya Prakash M (EE15D019)
Name of the Guide: Dr. Srirama Srinivas
Link: https://meet.google.com/ukx-qctw-xzd
Date/Time: 1st December 2022, 11.00am

Abstract
Multilevel inversion can be obtained using dual-inverter fed open end winding induction motor (OEWIM) drive. Field oriented control (FOC) and predictive current control (PCC) methods for the OEWIM drive with common-mode voltage (CMV) elimination are proposed. Both the proposed methods effectively control the speed of the OEWIM while eliminating the CMV in the dual inverter. Also, an improvised PCC method is proposed to completely obliterate the effect of the dead time in the OEWIM drive. The proposed PCC is formulated using a voltage based objective function instead of a conventional current based one. The candidate switching combinations for the evaluation of the objective function are thoughtfully chosen based on the position of the reference voltage vector to reduce the computational burden drastically, thereby improving the drive’s performance. Also, two improved PCC methods for the operation of the OEWIM drive with a single dc source and a floating capacitor, wherein a sector-based selection of the candidate switching combinations for the evaluation of the objective function are proposed that drastically reduced the computations, thereby facilitating a reduction in sampling time. Both the PCC methods effectively regulate the capacitor voltage, thus generating a symmetrical three-level voltage at the OEWIM terminals. Later, a weighting factor less cascaded PCC (CPCC) for the OEWIM drive with a single dc source and a floating capacitor bank is presented. Sequential evaluation of the objectives is introduced in this work, where the choice of the sequence of the control objectives is very critical. The second control objective is evaluated only for the two best cases obtained from the evaluation of the first objective. Unlike the generalized sequential predictive control, it is demonstrated that the system will completely collapse if the sequence of the control objectives is reversed. The proposed CPCC also uses a voltage based objective function with a sector-based selection of the candidate switching combinations to reduce the computational burden drastically.

All the methods proposed in the present work and analysed in detail, simulated and are experimentally verified.