sensorlesssrm_hossain2003

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 39, NO. 5, SEPTEMBER/OCTOBER 2003 1343

Four-Quadrant and Zero-Speed Sensorless Controlof a Switched Reluctance Motor

Syed A. Hossain, Member, IEEE, Iqbal Husain, Senior Member, IEEE, Harald Klode, Bruno Lequesne , Fellow, IEEE,Avoki M. Omekanda, Senior Member, IEEE, and Suresh Gopalakrishnan, Senior Member, IEEE

AbstractA four-quadrant sensorless controller for switchedreluctance motor (SRM) drives is presented in this paper. Thedrive system with appropriate turn-on and turn-off angles foreach operating quadrant delivers excellent dynamic performanceover a wide speed range including zero speed. The problemsassociated with practical implementation especially at low andzero speeds have been addressed and overcome with engineeringsolutions. Experimental results for a 1kW SRM obtained on adSPACE-based system are presented along with useful guidelinesfor practical implementation.

Index TermsFour-quadrant control, position and speed esti-mations, sensorless control, sliding-mode observer, switched reluc-

tance motors (SRMs), zero-speed control.

I. INTRODUCTION

SWITCHED reluctance motor (SRM) drives today aregradually penetrating the market with applications alreadydeveloped or being developed for the consumer product,

aerospace, and automobile industries. The SRM drives have the

attractive features of fault tolerance and the absence of magnets.

However, the control of an SRM depends on the commutation

of the stator phases in synchronism with the rotor position. The

position-sensing requirement increases the overall cost and

calls for extra space and complexity. This drawback excludes

the SRM from many cost sensitive industrial applications.Sensorless operation is a key requirement for the success of

SRM drives in various industries [1][4].

One method of sensorless operation is to detect the phase cur-

rent waveform and determine the rotor position by calculating

the phase inductance from rate of change of the phase current

[1], [2]. This method needs the injection of diagnostic pulses

into an inactive phase. However, the diagnostic pulses generate

Paper IPCSD 03059, presented at the 2002 Industry Applications SocietyAnnual Meeting, Pittsburgh, PA, October 1318, and approved for publica-tion in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the IndustrialDrives Committee of the IEEE Industry Applications Society. Manuscript sub-

mitted for review November 1, 2002 and released for publication May 31, 2003.This work was supported by a contract between Delphi and The University ofAkron.

S. A. Hossain was with the Department of Electrical Engineering, The Uni-versity of Akron, Akron, OH 44325-3904 USA. He is now with Globe Motors,Dayton, OH 45404-1249 USA (e-mail: [email protected]).

I. Husain is with the Department of Electrical Engineering, The University ofAkron, Akron, OH 44325-3904 USA (e-mail: [email protected]).

H. Klode is with the DaytonTechnical Center, DelphiE&C Systems, Dayton,OH 45408 USA (e-mail: [email protected]).

B. Lequesne, A. M. Omekanda, and S. Gopalakrishnan are withDelphi Research Labs, Shelby Township, MI 48315 USA (e-mail: [email protected];[email protected];[email protected]).

Digital Object Identifier 10.1109/TIA.2003.816541

a negative torque, and limit the resolution at high speed. Am-

plitude modulation [3] is another technique to obtain the rotor

position from modulated amplitude of the sensed current. How-

ever, this technique requires external hardware circuitry, which

adds cost and complexity to the system. Another simple sensor-

less technique is based on a currentfluxrotor position lookup

table [4]. Such an approach is simple and effective, but fails at

low and zero speeds due to the flux integrator problem. Addi-

tionally, this method demands a high-memory processor to store

a good resolution lookup table. The observer-based techniques

present an attractive alternativewhere terminal measurements ofphase voltages and currents are used to model the motor char-

acteristics and calculate the rotor position [5][7]. The design

and robustness analysis of sliding-mode-observer-based posi-

tion and speed estimation are well explained in [7].

Unfortunately, all of these studies focused exclusively on the

first quadrant operation: some methods are good for low and

medium speed only, while the rest are good for medium and

high speed only. The strategies provided are not sufficient for

highly dynamic loads, which require four-quadrant operation of

the SRM. The combination of two methods, one for low speed

and the other for high speed, may solve the problem. However,

it will increase the implementation complexity, and incur addi-

tional expense for a higher memory processor and better reso-lution current sensor.

Successful sensorless motor operation for a highly dy-

namic load demands four-quadrant sensorless operation of

the SRM including zero-speed position hold. In this paper,

a sliding-mode-observer-based sensorless technique [7] with

safeguards against observer stability, flux estimator accuracy,

model imperfection, and measurement noise is used for

four-quadrant sensorless operation. The primary focus is to

find the problems associated with practical implementation

and then to solve those for the development of a four-quadrant

sensorless controller that covers a wide speed range including

low- and zero-speed operation. The developed four-quadrant

sensorless drive system has been evaluated experimentally.

II. SYSTEM DESCRIPTION

The four-quadrant sensorless SRM drive consists of an

outer loop speed or torque controller and an inner loop current

controller. The current controller has appropriate turn-on and

turn-off angles for each operating quadrant, which are set based

on a chosen criterion such as torque-per-ampere maximization

or torque-ripple minimization [8]. The firing angle positions are

switched when the motor operation changes from one quadrant

0093-9994/03$17.00 2003 IEEE
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1344 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 39, NO. 5, SEPTEMBER/OCTOBER 2003

Fig. 1. Four-quadrant sensorless SRM drive.

to another. A sliding-mode-observer (SMO)-based position

and speed estimation method is used for sensorless control.

The block diagram of the system is given in Fig. 1.

A. Brief Review of SMO

A second-order SMO for the SRM of the following form is

considered:

(1)

where

with

Here, is the estimated position, is the estimated speed,

is the error function of measured flux and estimated flux

, and are the observer gains, and is the rotor po-

sition dependent term which can be considered as 1 for mo-

toring operation and 1 for generating operation.

The SMO-based sensorless operation was previously re-

ported for one-quadrant operation [7]. For dynamic actuator

type applications, four-quadrant operation is essential. The

dynamic load demands a small convergence rate of the observer

to enhance the robustness and the poles of the closed-loop

system should be chosen accordingly.

B. SRM Model and Control Strategy

An accurate, but simplified, SRM model is desired for the

model-based estimators. The following SRM flux model [9] ex-

pressed as a function of phase current and rotor position has

been used in the implementation:

(2)

where , , , ,

Here, is the number of turns per pole, is the number

of series paths, is the number of parallel paths, is the

stack length, is the stacking factor, is the radius to rotor

pole tips, is the air-gap length, is the total length of rotor

and stator pole, is the rotor pole width, is the iron per-meability, is the relative permeability, is the saturation

flux density, is the unaligned inductance, and is phase cur-

rent. The function is related to the unsaturated phase induc-

tance characteristics of the motor. The coefficient in is a

number between 01, which depends on the profile of the unsat-

urated phase inductance characteristics. The details of deriva-

tion of the value of from geometry and material properties

are described in [9]. Fig. 2 shows the comparison of fluxcur-

rent-position characteristics for measured and model data. The

solid lines represent the measured data, and the dotted lines rep-

resent the data obtained from the model.

A four-quadrant controller for SRM drives developed in [8]

with optimal turn-on and turn-off angles in each operating quad-rant for torque/ampere maximization is chosen for motor con-

trol. The firing angle positions are switched when the motor op-

eration changes from one quadrant to another.

C. Flux Estimator

The phase flux is estimated from the integral form of

Faradays law using phase current and phase voltage

measurements
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HOSSAIN et al.: FOUR-QUADRANT AND ZERO-SPEED SENSORLESS CONTROL OF SRM 1345

Fig. 2. Comparison of fluxcurrent-position characteristics for measured andmodel data.

The flux linkage integration is implemented in discrete time

using Euler Method

(3)

where is the sampling time, and are the flux

linkages at th and th sampling instants, and and

are the phase current and phase voltage at the th sampling

instant, respectively.

III. THEORETICAL AND PRACTICAL ASPECTS

A. Existence of Information

The observer subsystem is driven by the difference between

the observer output and the plant output. The region of existence

of sliding surface and the stability of the observer on the sliding

surface must be satisfied for proper operation of the observer. Atzero speed, if there is no phase excitation, the position estima-

tion becomes unstable due to the lack of information. Therefore,

the observer needs continuous information to function properly.

B. Zero-Speed Sensorless Operation

To avoid the unobservability at zero speed with no phase cur-

rent, a high-frequency bipolar speed is commanded, which will

dither the motor at a constant position. This allows extracting

information from the response of the system. The frequency of

command speed is chosen such that it allows transferring the

excitation from one phase to another. In effect, it consists of

phase-excitation dithering. This may obviously result in somerotor movement on the order of 15 . The dithering of rotor shaft

around a fixed position allows the elimination of flux estimator

integrator problem and the successful operation of observer.

Fig. 3 shows a comparison between the rotor angular position

measured with a 360-lines-per-revolution encoder and the esti-

mated position during zero-speed operation. The measured and

estimated position matches very well, one being on top of the

other, as shown in Fig. 3. The actual and estimated speeds are

also presented for comparison. A high-frequency square-wave

speed command between 2000 and 2000 r/min is applied for

the zero-speed position-hold test. Additional copper and iron

losses are generated due to the dithering around zero speed for

Fig. 3. Measured and estimated position and speed during speed inversion andzero-speed operation.

Fig. 4. Equivalent circuit for SRM.

constant position hold. The additional power losses have a neg-

ligible impact on the efficiency of the drive system.

C. Effect of Motor Losses

The phase current component contributing to the electro-

mechanical energy conversion must be separated from the

core loss component of phase current for greater accuracy

of position estimation in model-based estimators. In order to

model the effects of core losses, the phase voltage equation for

an SRM assuming a linear SRM model (i.e., ) is

considered

(4)

where is the phase resistance, and is the phase induc-tance. A resistive element to represent the core loss is con-

sidered in parallel with theback electromotive force (EMF) term

of (4) as shown in Fig. 4.

The energy balance equation from the equivalent circuit can

be expressed as

where is the total energy supplied by the electrical source,

is the winding loss, is the energy supplied to the elec-

tromagnetic field by the electrical system, is the core


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Fig. 5. Flow diagram for the modified flux observer.

losses, and is the energy converted from the electromag-

netic field. The phase current can be divided into two com-

ponents as

where and are the currents associated with the stored cou-

pling field energy and core losses, respectively. This is re-

sponsible for producing the energy associated with the energy

conversion loop. Therefore, the flux model needs to be modified

to

(5)

where , and is a core-loss-dependentparameter, and

it varies from 0.9 to 1.0 depending on the operating motor speed.

D. Modified Flux EstimatorThe common approach to estimate the flux is to integrate the

measured phase voltage according to (3). The method works

well in the higher speed range. However, at low and zero speeds

the voltage measurement noise and integration drift pose a sig-

nificant problem. The digital sampling error sometimes results

in zero flux estimation even when the phase current is nonzero.

The performance of the simplex flux observer has been im-

proved by incorporating the phase current information more

dominantly as follows.

1) The estimator output will be greater than zero if the phase

current is nonzero. The minimum value of the flux has

been set to the minimum theoretical level of .

where .

2) The saturation flux of the SRM is the flux linkage at

the aligned position when the motor draws the maximum

current.

At low speeds, the flux estimator output may exceed the sat-

uration flux due to measurement noise, which will make the

observer unstable. The effective solution is to reset the esti-

mator output at some reasonable value when the flux estimation

reaches . The reset value is chosen as

Fig. 6. Measured current, estimated current, and estimated flux using nominalintegrator.

Fig. 7. Measured current, estimatedcurrent,and estimatedfluxusingmodifiedintegrator.

is the aligned inductance and is the unaligned in-

ductance. The algorithm of the modified flux observer is given

in the flowchart of Fig. 5.

The estimated flux using the nominal integrator is observedto have saturated at 31 mWb in Fig. 6 due to integrator problem.

Consequently, the estimated current from estimated flux be-

comes unobservable. Fig. 7 shows the measured current, es-

timated current and estimated flux using modified integrator.

The flux estimator output was reset to when the integrator

output flux saturates to .

E. Voltage Measurement

During regeneration, the kinetic energy of the motor and

load is converted into electrical energy. Therefore, the capacitor

voltage rise due to regeneration must be considered for accurate

flux estimation. Fig. 8 shows the significant increase of the

phase voltage due to the increase of the dc-link bus voltage

from the nominal value during regeneration.

F. Reference Current Lower Limit

A reference current isgenerated to maintain the command

speed or position by regulating the phase currents. Sometimes

the outer loop controller may desire a zero reference current for

strong regulation of the command signal. The zero forces

zero phase currents and, consequently, the SMO becomes un-

observable due to nonexistence of information. For the SMO to

receive the continuous information, the lower limit of the

is set to a small current level of 1 A. This may lead to a small


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Fig. 8. Measured phase voltage for four-quadrant operation.

steady-state error in the outer loop controller, but the observ-

ability of the SMO will be continuously maintained.

G. Sensorless Starting

Although the time to reach the sliding surface for the ob-

server is finite, the error may be large at startup, leading to im-

proper phase excitation, hesitation and possibly reverse rotation.To overcome this undesirable effect, the motor is driven toward

the desired direction using preset phase voltages when the load

dynamic characteristics is somewhat known. The motor starts in

an open-loop fashion in a short time, which is sufficient for the

SMO to converge. However, the open-loop starting may fail for

a highly dynamic load.

H. Implementation of SMO

From the controls point of view, the chattering noise may in-

duce a problem in the estimation accuracy due to high innova-

tion gain. However, the chattering problems can be neglected

if the system time constant is higher than the controller exe-

cution time. For the proposed four-quadrant sensorless control,the execution time is 110 s. However, the rotor time constant

is at least ten times higher than the execution

time. Therefore, the chattering noise does not affect the esti-

mated position.

I. Comparison With Table-Based Approach

In comparison with the conventional flux-current-rotor po-

sition lookup-table-based rotor position estimation technique,

the SMO-based approach delivers a robust estimation of posi-

tion and speed. The SMO exhibits high degree of robustnessin the face of model uncertainty, parameter variation, initial

rotor position error, and load torque disturbance, and possessesan automatic adaptation property with respect to the intensity

of measurement noise [10]. The lookup-table-based approach

is highly dependent on the accuracy of the static characteris-

tics of the machine. The error in flux estimation or model un-

certainty will easily lead to error in position estimation. Fur-

thermore, the motor speed in the lookup-table-based method is

obtained by differentiating the position, which may lead to sta-

bility problems during four-quadrant operation in the case of er-

roneous position estimation. On the other hand, the modification

in flux estimation helps the SMO to be observable at zero-speed

crossing, enabling the SMO to give both the rotor position and

speed simultaneously.

Fig. 9. Hardware setup for SRM drive system.

Fig. 10. Measured and estimated speed for four-quadrant speed control.

Fig. 11. Measured and estimated position during speed inversion.

IV. EXPERIMENTAL RESULTS

The prototype setup to verify the four-quadrant sensorless

control method experimentally is shown in Fig. 9. The test setup

was designed for motion control applications, which can beoperated in the variable-speed-controlled or position-controlled

loop. The controller algorithm has been implemented within a

dSPACE rapid prototyping platform. The classic bridge power

converter was used to meet the commutation requirements.

Relevant experimental results showing the performance of the

proposed sensorless scheme are presented. The SRM drive

was operated in closed-loop four-quadrant mode completely

sensorlessly using the position and speed information obtained

from the observer. Position information from an encoder is

presented for comparison only.

Figs. 10 and 11 show a comparison between the measured po-

sition and estimated position, and measured speed and estimated
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Fig. 12. Measured current, estimated current, and estimated flux in the first orthird quadrant current-controlled mode.

Fig. 13. Measured current, estimated current, and estimated flux in thevoltage-controlled mode.

Fig. 14. Measured current, estimated current, and estimated flux at secondquadrant operation.

speed, respectively, during motor speed inversion. A speed ref-erence switching from 3500 to 3500 r/min is applied, necessi-

tating four-quadrant operation of the drive system. The rotor po-

sition has been wrapped to confine measurement and estimation

within one electrical cycle. In the first and third quadrants, the

motor operates above the base speed. The measured current, es-

timated flux, andthe estimated current duringthe current control

mode and single-pulse mode for first or third quadrant operation

are presented in Figs. 12 and 13, respectively. Fig. 14 shows the

flux and current estimation for second quadrant operation. Fi-

nally, Fig. 15 shows the position estimation of the system oper-

ating at a constant, but very low speed. The speed reference in

this case is 60 r/min.

Fig. 15. Measured and estimated position at 60 r/min.

The larger difference in the measured and estimated currents

at higher speeds (Fig. 13) is due to modeling imperfections.

At higher speeds, the motor operates in the voltage-controlled

mode with lower current magnitudes. The flux value from the

motor model at lower current levels differs significantly from

the actual value for a given current as can be seen from Fig. 2.This effect is reflected in the measured and estimated current

of Fig. 13. However, the SMO is robust enough to overcome

the model inaccuracy and provide correct position and speed

information.

V. CONCLUSION

This paper presented a four-quadrant sensorless controller de-

veloped in a test bench considering the practical implementa-

tion issues. The motor speed command was toggled from one

rotational direction to another through zero speed without any

mechanical position sensor. The rotor position of the SRM is es-

timated at zero operating speed by imposing a high-frequency

speed command. The flux estimator and the SR motor modeling

imperfection were modified to reduce the cumulative error at

zero and low speeds. The experimental results demonstrate the

feasibility of the proposed four-quadrant sensorless scheme.

REFERENCES

[1] W. D. Harris and J. H. Lang, A simple motion estimator for variablereluctance motors, IEEE Trans. Ind. Applicat., vol. 26, pp. 237243,Mar./Apr. 1990.

[2] S. R. MacMinn, W. J. Rzesos, P. M. Szczesny, and T. M. Jahns, Ap-plication of sensor integration techniques to switched reluctance motordrives, IEEE Trans. Ind. Applicat., vol. 28, pp. 13391344, Nov./Dec.1992.

[3] M. Ehsani, I. Husain, S. Mahajan, and K. R. Ramani, New modulation

techniques for rotor position sensing in switched reluctance motors,IEEE Trans. Ind. Applicat., vol. 30, pp. 8591, Jan./Feb. 1994.

[4] J. P. Lyons, S. R. MacMinn, and M. A. Preston, Flux/current methodsfor SRM rotor position estimation, in Conf. Rec. IEEE-IAS Annu.

Meeting, Dearborn, MI, 1991, pp. 482487.[5] A. Lumsdaine and J. H. Lang, State observers for variable reluctance

motors, IEEE Trans. Ind. Electron., vol. 37, pp. 133142, Apr. 1990.[6] I. Husain, S. Sodhi, and M. Ehsani, Sliding mode observer based

control for switched reluctance motors, in Conf. Rec. IEEE-IAS Annu.Meeting, Denver, CO, 1994, pp. 635643.

[7] R. McCann, M. S. Islam, and I. Husain, Application of sliding modeobserver for switched reluctance motor drives, IEEE Trans. Ind. Ap-

plicat., vol. 37, pp. 5158, Jan./Feb. 2001.[8] S. A. Hossain, I. Husain, H. Klode, B. Lequesne, and A. Omekanda,

Four-quadrant control of switched reluctance motor for a highly dy-namic actuator load, in Proc. IEEE APEC, vol. I, Dallas, TX, Mar.2002, pp. 4147.


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[9] S. A. Hossain and I. Husain, A geometry based simplified analyticalmodel of switched reluctance machines for real-time controller imple-mentation, in Proc. IEEE PESC, Cairns, Australia, June 2002, pp.839844.

[10] M. S. Islam, I. Husain, R. J. Veillette, and C. Batur, Design and per-formance analysis of sliding-mode observers for sensorless operationof switched reluctance motors, IEEE Trans. Contr. Syst. Technol., sub-mitted for publication.

Syed A. Hossain (S01M02) received the B.Sc.and M.Sc. degrees in electrical and electronic engi-neering from Bangladesh University of Engineeringand Technology, Dhaka, Bangladesh, in 1994 and1997, respectively, and the Ph.D. degree in electricalengineering from The University of Akron, Akron,OH, in 2002.

From 1994 to 1998, he was a Lecturer and thenan Assistant Professor at Bangladesh University ofEngineeringand Technology. In the summers of 2000and2001, he waswith DelphiResearch Laboratories,

Shelby Township, MI. He is currently a Senior Project Engineer with GlobeMotors, Dayton, OH, where he is engaged in the design and development ofcontrols for brushless motors. His technical interests include the developmentof high-performance brushless motor servo drives for automotive applications.

Iqbal Husain (S89M89SM99) receivedthe B.Sc. degree from Bangladesh University ofEngineering and Technology, Dhaka, Bangladesh,in 1987, and the M.S. and Ph.D. degrees from TexasA&M University, College Station, in 1989 and 1993,respectively, all in electrical engineering.

He is currently a Professor in the Department ofElectrical and Computer Engineering, The Univer-sity of Akron, Akron, OH, engaged in teaching andresearch. He was a summer researcher at WrightPatterson AFB Laboratories in 1996 and 1997.

Previously, he was a Lecturer at Texas A&M University and also a ConsultingEngineer with Delco Chassis, Dayton, OH. His research interests are in theareas of control and modeling of electrical drives, design of electric machines,and development of power conditioning circuits. He has worked extensively

in the development of switched reluctance motor drives, including sensorlesscontrollers.

Dr. Husain received the 2000 IEEE Third Millennium Medal and the 1998IEEE Industry Applications Society Outstanding Young Member Award. He isalso the recipient of three IEEE Committee Prize Paper Awards.

Harald Klode received the Dipl. Ing. degree inelectrical engineering from the Rheno-WestphalianSchool of Technology (RWTH), Aachen, Germany,in 1984.

In 1985, he was a Research Assistant in the De-partment of Electrical and Computer Engineering,University of Colorado, Boulder. From 1986 until1988, he was with the General Motors ResearchLaboratories, Warren, MI, working in the areas of

electromechanical actuators and motors for vehicularsystems. He continued his work on various brush,

brushless, and SR motor-and-actuator-related projects at Delco Products,Delphi Chassis, ITT Automotive, and VALEO in Dayton, OH. In 1999, he joined Delphis Technical and Innovation Center in Dayton, OH, where he iscurrently a Senior Research Engineer and Team Leader for Advanced MotorDevelopment for Controlled Braking Systems. He is the holder of severalU.S. and international patents and has published papers in the areas of electricmotors. His current interest is focused on the development of mechatronics andactuators for automotive applications.

Bruno Lequesne (M85SM89F97) received theCertified-Engineer degree from the Ecole SuprieuredElectricit, Gif-sur-Yvette, France, in 1978, and thePh.D. degree in electrical engineering from the Uni-versity of Missouri, Rolla, in 1984.

His is currently a Senior Staff Research Engineerwith Delphi Research Labs, Shelby Township, MI.His research interests are in the areas of electricalautomotive systems, drive-by-wire mechatronic sys-

tems, power generators, sensors, and related issues.He is the holder of 25 patents, primarily on sensors and linear actuators.Dr. Lequesne is the recipient of several Best Paper Awards from the IEEE

Industry Applications Society (IAS), its Electrical Machines Committee, andthe Society of Automotive Engineers.

Avoki M. Omekanda (M95SM97) receivedthe bachelors degree in physics from MohammedV University, Rabat, Morocco, in 1984, and the

Engineer and Ph.D. degrees in electrical engineeringfrom the Facult Polytechnique de Mons, Mons,Belgium, in 1987 and 1993, respectively.

Following the receipt of the Engineers diploma,he worked for A.C.E.C Corporation, Charleroi, Bel-gium. In January 1990, he joined the Facult Poly-technique de Mons as a Research Engineer. His re-search interests included computer-aided design for

switched reluctance machines and magnetic field computation using numer-ical methods. After receiving the Ph.D. degree, he was an Assistant Professorin the Electrical Engineering Department, Facult Polytechnique de Mons, fortwo years. In June 1995, he joined the General Motors Research and Develop-ment Center, Warren, MI, as a Senior Research Engineer. In 1999, he becamepart of Delphi Research Labs, Shelby Township, MI, where he is currently aStaff Research Engineer. His research interests include design, analysis, andcontrol of electric machines, in particular, switched reluctance, for automotiveapplications.

Dr. Omekanda is a Member of the Association des Ingnieurs de Mons (Bel-gium) and Socit des Electriciens et des Electroniciens (France).

Suresh Gopalakrishnan (S95M00SM03)received the B.E. degree from Annamalai University,Annamalai Nagar, India, in 1989, the M.S. degreefrom Indian Institute of Technology, Chennai, India,in 1992, and the Ph.D. degree from Texas A&M

University, College Station, in 2000, all in electricalengineering.

From June 1992 to August 1995, he was with theR&D department of Kirloskar Electric Company,Bangalore, India. In January 2000, he joined theMechatronics Group at Delphi Corporation, Shelby

Township, MI, where he is involved with automotive power electronics andmotor drive applications. His research interests include power electronics, con-trol of variable-speed motor drives, and microcontroller and DSP applicationsin automotive actuators.

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