Open AccessMode recognition and coordinated magnetisation control method for variable flux memory machine
Author(s) -
Wang Wei,
Lin Heyun,
Yang Hui,
Lyv Shukang,
Liu Wei,
Fang Shuhua
Publication year - 2021
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12194
Subject(s) - mode (computer interface) , control theory (sociology) , magnet , torque , magnetization , computer science , variable (mathematics) , artificial neural network , flux (metallurgy) , current (fluid) , artificial intelligence , engineering , control (management) , mathematics , physics , materials science , magnetic field , electrical engineering , mathematical analysis , quantum mechanics , thermodynamics , operating system , metallurgy
The hybrid permanent magnet (PM) variable flux memory machine employs high‐ and low‐coercive‐force hybrid PMs to simultaneously obtain a high torque density and regulable PM flux property. The operating trajectories and steady working‐points of this type of machine switch back and forth in multiple regions. To identify operating modes under various PM magnetisation states and speed ranges, this paper proposes a mode recognition and coordinated control method based on probabilistic neural networks (PNNs). A PNN algorithm is trained offline and executed in real‐time to obtain a certain operating mode with the maximum probability of current state. According to the mode recognition result, a coordinated control scheme for applying short‐time pulses or continuous flux‐weakening current in a reasonable manner is presented. The proposed method exhibits an excellent capability in real‐time operating modes identification, hence achieving magnetisation current control of multiple modes easily. Its feasibility and effectiveness are validated by experimental results on a hybrid PM VFMM prototype.