DocumentCode :
3603625
Title :
Loss Manipulation Capabilities of Deadbeat Direct Torque and Flux Control Induction Machine Drives
Author :
Yukai Wang ; Ito, Takumi ; Lorenz, Robert D.
Author_Institution :
Wisconsin Electr. Machines & Power Electron. Consortium, Univ. of Wisconsin-Madison, Madison, WI, USA
Volume :
51
Issue :
6
fYear :
2015
Firstpage :
4554
Lastpage :
4566
Abstract :
This paper investigates the loss manipulation capabilities of deadbeat direct torque and flux control (DB-DTFC) induction machine drives. For each switching period, a volt-second-based inverse model provides a range of volt-second solutions to achieve the desired torque at the end of each switching interval, whereas the stator flux magnitude provides another degree of freedom to manipulate machine losses. With a flux-based DB-DTFC loss model proposed, losses can be manipulated each switching period without compromising torque dynamics. For a steady-state operation and typical process trajectories, the minimum loss can be achieved with corresponding energy savings. Alternatively, significant losses can be rapidly induced to dissipate kinetic energy in a machine during braking transients. This loss maximization technique provides significant braking torque without requiring additional hardware to transfer/dissipate energy. DB-DTFC induction machine drives provide an effective and elegant solution for continuous loss manipulation without compromising dynamic performance.
Keywords :
induction motor drives; magnetic flux; magnetic variables control; torque control; deadbeat direct torque control; flux control; induction machine drives; loss manipulation; minimum loss; steady state operation; switching period; torque dynamics; Couplings; Induction machines; Iron; Minimization; Rotors; Stators; Torque; AC motor drive; braking; direct torque control; flux linkage based; induction machine; loss distribution; loss minimization control; loss model;
fLanguage :
English
Journal_Title :
Industry Applications, IEEE Transactions on
Publisher :
ieee
ISSN :
0093-9994
Type :
jour
DOI :
10.1109/TIA.2015.2455030
Filename :
7154453
Link To Document :
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