K. Malekian, J. Milimonfared, B. Majidi,
Volume 5, Issue 1 (3-2009)
Abstract
The main theme of this paper is to present novel controller, which is a genetic
based fuzzy Logic controller, for interior permanent magnet synchronous motor drives with
direct torque control. A radial basis function network has been used for online tuning of the
genetic based fuzzy logic controller. Initially different operating conditions are obtained
based on motor dynamics incorporating uncertainties. At each operating condition, a
genetic algorithm is used to optimize fuzzy logic parameters in closed-loop direct torque
control scheme. In other words, the genetic algorithm finds optimum input and output
scaling factors and optimum number of membership functions. This optimization procedure
is utilized to obtain the minimum speed deviation, minimum settling time, zero steady-state
error. The control scheme has been verified by simulation tests with a prototype interior
permanent magnet synchronous motor.
J. Soleimani, A. Vahedi, S. M Mirimani,
Volume 7, Issue 4 (12-2011)
Abstract
Recently, Inner permanent magnet (IPM) synchronous machines have been
introduced as a possible traction motor in hybrid electric vehicle (HEV) and traction
applications due to their unique merits. In order to achieve maximum torque per ampere
(MTPA), optimization of the motor geometry parameters is necessary. This paper Presents
a design method to achieve minimum volume, MTPA and minimum value of cogging
torque for traction IPM synchronous machines and simulation in order to extract the output
values of motor is done using 3D-Finite Element Model, that has high level of accuracy and
gives us a better insight of motor performance. Then presents back EMF, power factor,
cogging torque, Flux density, torque per ampere diagram, CPSR (constant power speed
ratio), torque per speed diagram in this IPM synchronous machine. This study can help
designers in design approach of such motors.
