We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Flux-weakening fuzzy adaptive ST-SMO sensorless control algorithm for PMSM in EV.
- Authors
Wang, Yongwei; Wu, Jingbo; Guo, Zhijun; Xie, Chengwei; Liu, Junjie; Jin, Xin
- Abstract
Aiming at the sensorless control system of Permanent Magnet Synchronous Motor (PMSM) for the pure Electric Vehicle (EV), the issues of slow convergence, phase delay, and chattering caused by Sliding Mode Observer (SMO), a single current flux weakening fuzzy adaptive Super-Twisting (ST) SMO algorithm is proposed in this paper. The fuzzy adaptive algorithm is used to estimate the uncertain boundary and adaptively adjust sliding mode gain, which is used in the ST algorithm to accelerate the convergence speed of sliding mode gain, and eliminate the system delay caused by phase-locked loop and phase compensation, and improve the estimation accuracy of speed and rotor position. The single current flux weakening is used to improve the issues of d-q axis current coupling and enhance the load capacity of the field weakening area of the PMSM. The algorithm is verified by MATLAB/Simulink. The simulation results show that the single current flux-weakening fuzzy ST-SMO algorithm has faster convergence speed in the variable speed and the variable load of PMSM sensorless control system, which has significantly reduced chattering, obtained more accurate speed and rotor position, and has better dynamic response and robustness, and has widened the speed region of PMSM.
- Subjects
SENSORLESS control systems; ELECTRIC vehicles; PERMANENT magnet motors; FUZZY algorithms; PHASE-locked loops; ELECTRIC automobiles
- Publication
Journal of Supercomputing, 2022, Vol 78, Issue 8, p10930
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-021-04264-8