Journal of Shanghai University(Natural Science Edition) ›› 2018, Vol. 24 ›› Issue (6): 861-876.doi: 10.12066/j.issn.1007-2861.1890

• Research Paper • Previous Articles     Next Articles

Improved model predictive direct torque control for asynchronous machine

SONG Wenxiang(), LE Shengkang, WU Xiaoxin, RUAN Yi   

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
  • Received:2017-01-21 Online:2018-12-30 Published:2018-12-24
  • Contact: SONG Wenxiang E-mail:wxsong@shu.edu.cn

Abstract:

This paper proposes an improved model predictive direct torque control (MPDTC) method. An optimal voltage vector selector is obtained by analyzing relationship between stator flux and torque, which can be used to calculate the desired voltage vector based on the stator flux and torque reference. The method only needs to evaluate three voltage vectors in a sector of the desired voltage vector. As a result, the computational burden of conventional MPDTC is reduced effectively. Time delay introduced in computation can cause the stator current to oscillate around its reference and increase current and torque ripples. To solve the problem, a delay compensation method is used. Furthermore, switching frequency of the inverter is reduced significantly by introducing a constraint of power semiconductors switching number to the cost function of MPDTC. Both simulation and experimental results are presented to verify validity and feasibility of the proposed method.

Key words: asynchronous machine, direct torque control, delay compensation, model predictive control, low switching frequency

CLC Number: