IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 50, NO. 6, NOVEMBER/DECEMBER 2014 1
A Fixed Switching Frequency Predictive Current
Control Method for Switched Reluctance Machines
Rajib Mikail, Student Member, IEEE, Iqbal Husain, Fellow, IEEE, Yilmaz Sozer, Member, IEEE,
Mohammad S. Islam, Senior Member, IEEE, and Tomy Sebastian, Fellow, IEEE
Abstract—The paper presents a novel fixed switching frequency
predictive current control method for switched reluctance ma-
chines (SRM). The proposed deadbeat predictive current con-
troller accurately predicts the required duty ratio for the PWM
pulse for a given reference current in each digital time step over
the entire speed range of operation. The pulse width depends
on the operating conditions, machine parameters and the rotor
position. The controller utilizes the machine inductance profile as
a function of current and rotor position to accurately predict the
required voltage. The control method is studied through computer
simulation and followed by experimental validation. The method is
suitable for torque ripple sensitive applications requiring accurate
tracking of a given current profile and mitigating the audible noise
due to the switching of the inverter.
Index Terms—Back EMF, deadbeat controller, fixed frequency,
hysteresis control, incremental inductance, nonlinear model, pre-
dictive control.
I. I NTRODUCTION
A
switched reluctance machine produces torque with inde-
pendent phase control. The current required in each phase
depends on the torque demand in torque controlled applica-
tions. Each phase has its own command current as a function of
position depending on the control algorithm. For applications
requiring smooth torque production, the torque ripple control
algorithm has to perform within the specifications over the
entire speed range. The primary objectives of these applications
are low torque ripple, low acoustic noise and low unbalanced
magnetic force that contributes to vibration, and fast posi-
tion, speed and torque responses. Various control methods for
smooth torque production have evolved for SRM over the past
few decades. These include current-profiling-based control [1]–
[3], feedback linearized and decoupled control [4]–[6], direct
torque control (DTC) [7], [8], iterative-learning-based control
Manuscript received September 7, 2013; revised January 20, 2014; accepted
February 28, 2014. Paper 2013-EMC-633.R1, presented at the 2012 IEEE En-
ergy Conversion Congress and Exposition, Raleigh, NC, USA, September 15–
20, and approved for publication in the IEEE TRANSACTIONS ON I NDUSTRY
APPLICATIONS by the Electric Machines Committee of the IEEE Industry
Applications Society.
R. Mikail was with North Carolina State University, Raleigh, NC 27606
USA. He is now with ABB Inc., Raleigh, NC 27606 USA (e-mail: rajib.
mikail@us.abb.com).
I. Husain is with North Carolina State University, Raleigh, NC 27606 USA
(e-mail: ihusain2@ncsu.edu).
Y. Sozer is with the The University of Akron, Akron, OH 44325 USA
(e-mail: ys@uakron.edu).
M. S. Islam and T. Sebastian are with Halla Mechatronics, Bay City,
MI 48706 USA (e-mail: mohammad.s.islam@ieee.org; t.sebastian@ieee.org).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIA.2014.2322144
(ILC) [9], fuzzy- and neural-network-based control [10], [11],
control with torque-sharing functions (TSF) [12], and sliding-
mode-observer-based control [13], [14]. Feedback linearizing
and decoupled control method [4]–[6] introduces a transforma-
tion to convert a nonlinear system into an equivalent linear one.
It is suitable for high performance applications, but only when
an accurate model of the machine is available. The system can
become unstable with less accurate models. The digital real-
time implementation is feasible only at lower speeds. DTC,
ILC, fuzzy, sliding mode and neural network based control
methods also suffers from instability at higher speeds.
Several of the control algorithms depend on shaping the
phase currents to produce a smooth torque profile. Control
algorithms that compensate for torque fluctuations throughout
the conduction interval precisely depend on online or offline
current waveforms. Online methods work on the basis of calcu-
lating a reference or command current instantaneously, while
in offline methods, the current commands are fetched from
a pre calculated look-up table. These command currents are
established in the phases by a high bandwidth current regulator.
In most of the control methods mentioned, the final block of
the algorithm incorporates a current controller as a final step.
The common methods for current control are the hysteresis
[2], [9], [10], [15] and PI controllers [16] or a hybrid type of
control [17]. A soft chopping current control method has been
proposed in [18]. The dynamic performance of these controllers
deteriorates at higher speeds. The hysteresis type current con-
troller, in general, has better dynamic performance, but the
problem of varying frequency restricts its use in many appli-
cations where acoustic noise due to switching is undesirable.
The PI current controller has the advantage of fixed switching
frequency. Speed and position dependent PI constants result in
better control at higher speeds but this increases the complexity
of the controller.
In the digital implementation of the hysteresis current con-
troller, the voltage command of the inverter is updated at the
end of each control loop time-period. The current may deviate
from its reference for the entire digital time period which will
increase the torque ripple especially during commutation from
one phase to the next one. The switching frequency is not
constant as shown in Fig. 1. The switching frequency of the
inverter could fall within the audible range which would lead to
acoustic noise problems. In a PI controller, several digital time
steps are required to respond to a step change in command.
At higher speeds, the system cannot utilize the full control
bandwidth available from the converter due to the poor dynamic
performance and the stability issue of the PI controller itself.
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