Open AccessAverage torque control of switched reluctance machine drives for electric vehicles
Author(s) -
Cheng He,
Chen Hao,
Yang Zhou
Publication year - 2015
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/iet-epa.2014.0424
Subject(s) - switched reluctance motor , torque , control theory (sociology) , torque ripple , direct torque control , engineering , acceleration , estimator , process (computing) , computer science , control engineering , automotive engineering , voltage , control (management) , rotor (electric) , mathematics , mechanical engineering , physics , electrical engineering , classical mechanics , artificial intelligence , induction motor , thermodynamics , statistics , operating system
Instantaneous torque control and average torque control (ATC) strategies of switched reluctance machine (SRM) are comparatively investigated to select appropriate control mode for the application of SRM in electric vehicles (EVs). Three novel methods are put forward to optimise ATC for meeting the performance requirements of EVs. On‐line estimator is designed to estimate the average torque of SRM in real‐time and improve the steady‐state torque precision. Current chopping control‐angle position control hybrid crossover control is proposed to widen the adjustable speed range and improve the process smoothness of SRM in consideration of acceleration and deceleration. Turn‐on and turn‐off angles of SRM are optimised by generic algorithm to enhance driving efficiency and reduce torque ripple. At last, the three proposed control methods are validated by simulations and experiments.