SlideShare a Scribd company logo
David C. Wyld et al. (Eds) : DBDM, CICS, CSIP, AI&FL, SCOM, CSE, CCNET-2016
pp. 37–44, 2016. © CS & IT-CSCP 2016 DOI : 10.5121/csit.2016.60504
A NEW APPROACH TO DTC METHOD
FOR BLDC MOTOR ADJUSTABLE SPEED
DRIVES
Fatih Korkmaz
Department of Electric-Electronic Engineering, Çankırı Karatekin University,
Uluyazı Kampüsü, Çankırı, Turkey
ABSTRACT
This paper proposes a new approach to direct torque control (DTC) method for brushless direct
current (BLDC) motor drives. In conventional DTC method, two main reference parameters are
used as: flux and torque. In this paper, the new approach has been proposed to improve the
BLDC motor dynamic performance. A main difference from the conventional method of it was
that only one reference parameter (speed) was used to control the BLDC motor and the second
control parameter (flux) was obtained from speed error through the proposed control
algorithm. Thus, the DTC performance has been especially improved on systems which need
variable speed and torque during operation, like electric vehicles. The dynamic models of the
BLDC and the DTC method have been created on Matlab/Simulink. The proposed method has
been confirmed and verified by the dynamic simulations on different working conditions.
KEY WORDS
Brushless machines, Direct torque control, Vector control, Torque control
1. INTRODUCTION
In recent years, the BLDC motors applications become more popular in industrial and daily
utilization, like CNC machines, servo systems and electric vehicles. The main reasons of the
increasing on popularity of BLDC motors, in other words, main advantages of the BLDC motors,
can be listed as follows[1-4]:
• High efficiencies
• High power densities
• High starting torque
• Wide speed ranges
• Linear torque and speed characteristics
• Low maintenance and works in any condition
The BLDC motors not only have advantages of conventional DC motors but also have advantages
of AC motors as can be seen from the list. Because, they have the AC motor mechanical structures
–no brushes or collectors–while they have the DC motors electrical structures.
The DTC method was developed by Takahashi in the middle of the 1980s, for three phase induction
motors. The DTC method converts three phase parameters of the motor (three phase voltage and
currents) to two phase independent vector components with Clarke transformation, thus, it proposes
38 Computer Science & Information Technology (CS & IT)
control of every components separately, like conventional DC motors. Although, it was developed
for the induction motors, it has been applied many other motor types like permanent magnet AC
motors, BLDC motors, switched reluctance motors, linear motors[5-6].
In literature, many kind of BLDC motor drive methods can be found. In [7], artificial neural
networks based method was used in modeling of BLDC to get the maximum power consumption.
Very simple and effective three-level neutral point clamped inverter was proposed to drive axial
flux BLDC motors, in [8]. Field Programmable Gate Array (FPGA) based BLDC motor driver with
using digital pulse-width modulation (PWM) is presented in [9]. In addition, several different
methods, which based of the DTC, were studied in BLDC drivers. Reference [10] proposes the
DTC method for matrix converter fed BLDC motor. The DTC of BLDC motor method using with
four-switch inverter in constant torque region was proposed in [11].
In this paper, a new approach to the DTC method has been proposed for small sized electric
vehicles that work in variable speed and torque conditions, naturally. In the proposed method,
optimum stator flux reference value was obtained by PI controller with usage of the speed error.
The dynamic model of the proposed method was developed with Matlab/Simulink. The dynamic
simulations were performed and results were presented to illustrate the validity of the proposed
method.
2. DIRECT TORQUE CONTROL OF BLDC
The BLDC motor has three phase stator windings with permanent magnet rotor and electrical model
of the motor that connected with PWM inverter, is given in Fig. 1[12].
Voltage equations of the motor can be obtained by the following equation;
൥
Vୟ
Vୠ
Vୡ
൩ = ൥
R 0 0
0 R 0
0 0 R
൩ ൥
iୟ
iୠ
iୡ
൩ + ൥
L 0 0
0 L 0
0 0 L
൩
ୢ
ୢ୲
൥
iୟ
iୠ
iୡ
൩ + ൥
eୟ
eୠ
eୡ
൩ (1)
Where Vୟ, Vୠ, Vୡ are phase voltages, R is resistance, L is phase inductance, iୟ, iୠ, iୡ are phase
currents and eୟ, eୠ, eୡ are back EMFs.
Figure 1. Electrical model of the motor that connected with PWM inverter
The mechanical moment equation of the motor given by the following equation;
Tୣ = T୐ + Bω୫ + j
ୢωౣ
ୢ୲
(2)
Tୣ and T୐ describes generated electromagnetic torque and load torque, respectively. B is the friction
Computer Science & Information Technology (CS & IT) 39
coefficient, j is the inertia and ω୫ is the angular velocity of rotor[13].
The DTC method needs to transformation of the three phase motor parameters to two phase. In this
transformation, electrical parameters of the motor (voltages, currents, back emf) should to be
transformed to stationary reference frame and it can also be named as α − β transformation or
Clarke transformation in many sources. The Clarke transformation matrix is given (3).
൤
fα
fβ
൨ =
ଶ
ଷ
቎
1 −
ଵ
ଶ
−
ଵ
ଶ
0
√ଷ
ଶ
−
√ଷ
ଶ
቏ ൥
fୟ
fୠ
fୡ
൩ (3)
Where, fα, fβ are α − β components of motor parameters, and fୟ, fୠ, fୡ are the abc frame
components [14].
With the transforming of the three phase parameters of the motor, α − β components of the phase
voltages can be written as:
vୱα = Rୱiୱα + Lୱ
ୢ୧౩α
ୢ୲
+ eα (4)
vୱβ = Rୱiୱβ + Lୱ
ୢ୧౩β
ୢ୲
+ eβ (5)
Where vୱα, vୱβ are the stator voltages, iୱα, iୱβ are the stator currents and eα, eβ are back emf in the
α − β referance frame.
In the DTC scheme, stator flux components are obtained from α − β components of the measured
stator voltages and currents as given below[15]:
λୱα = ‫׬‬ሺvୱα − Rୱiୱαሻdt (6)
λୱβ = ‫׬‬൫vୱβ − Rୱiୱβ൯dt (7)
The magnitude of the flux can be calculated with;
λ = ටλୱα
ଶ
+ λୱβ
ଶ
(8)
and position of the stator flux vector can be calculated with;
θ = arctan
λ౩β
λ౩α
(9)
In the conventional DTC (C-DTC) method, control algorithms works with two separate reference
values as torque (or speed) and flux references. Because, in idea of the DTC, stator flux vector has
two components (α − β components) and they can be controlled independently from each other.
One of them controls flux, while the other one controls torque. In generally, flux reference is kept
constant and the speed control of the motor can be achieved by setting up the torque reference
value. This approach is very appropriate for constant torque-variable speed applications. The
conventional DTC block diagram is given in Fig. 2.
40 Computer Science & Information Technology (CS & IT)
Figure 2. The conventional DTC block diagram
3. ADAPTIVE FLUX BASED METHOD
A main difference from the conventional method of it was that only one reference parameter (speed)
was used to control the BLDC motor and the second control parameter (flux) was obtained from
speed error through the proposed control algorithm. Thus, the DTC performance has been especially
improved on systems which need variable speed and torque during operation, like electric vehicles.
The dynamic models of the BLDC and the DTC method have been created on Matlab/Simulink.
The proposed DTC method Simulink block diagram is given in Fig. 3.
In dynamic simulations, the BLDC motor was performed under two different working conditions.
The parameters of the blocks and the motor that used in dynamic simulations were given in
appendix. Total simulation time was 1 sec. for all conditions. The sampling time was 10 µs.
The motor load constant (5Nm) and the speed reference was changed 2000 rpm to 400 rpm at 0,5.
sec. in first working condition. The speed and the torque responses of the motor were given in Fig. 4
and Fig. 5, respectively.
Figure 3. The proposed DTC Simulink block diagram
Computer Science & Information Technology (CS & IT)
Figure 4. Speed responses
Figure 5. Torque responses
Figure 6. Speed responses
Computer Science & Information Technology (CS & IT)
Speed responses of the BLDC in variable speed-constant load
Torque responses of the BLDC in variable speed-constant load
Speed responses of the BLDC in variable torque-constant speed
41
constant speed
42 Computer Science & Information Technology (CS & IT)
Figure 7. Torque responses
In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque
reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the
motor were given in Fig. 6 and Fig.
It can be seen in from figures (Fig. 4
improved with the P-DTC method. The torque and speed ripples reduced remarkably with the P
DTC method especially in high speed reference values. In 400 rpm speed refe
dynamic behaviors were almost same with both methods.
4. CONCLUSIONS
Over the last decades, the BLDC motors have been used many industrial applications and it has gain
great popularity between electric motors. On the other hand, the DTC is well
performance control method not only for induction motors but also many other motor types.
paper presents a new perspective to the
applied to the BLDC motors which considered
works in variable speed and torque conditions with single referenc
DTC method was modified with the adding of second PI controller that produces optimum flux
reference. In order to test the
simulations were been performed und
The simulations results showed that the proposed method reduced remarkably the speed and the
torque ripples when compared conventional DTC method. The proposed method
simple structure to apply the conventional DTC and its extra computational load to the contro
was almost zero.
APPENDIX
The parameters of the blocks and the motor that used in dynamic simulations are
400V, stator phase resistance, Rs (ohm) = 0.45, stator
hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32
weber, sampling time 10 µsec.
REFERENCES
[1] C. Xia, Z. Li, and T. Shi, “A Control Strategy for Four
Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058
2009.
Computer Science & Information Technology (CS & IT)
Torque responses of the BLDC in variable torque-constant speed
In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque
reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the
and Fig. 7, respectively.
from figures (Fig. 4–Fig. 7) that, the BLDC motor speed and torque responses were
DTC method. The torque and speed ripples reduced remarkably with the P
DTC method especially in high speed reference values. In 400 rpm speed reference, the motor
dynamic behaviors were almost same with both methods.
, the BLDC motors have been used many industrial applications and it has gain
great popularity between electric motors. On the other hand, the DTC is well
performance control method not only for induction motors but also many other motor types.
paper presents a new perspective to the conventional DTC method. The proposed DTC method
the BLDC motors which considered drives small size electric vehicles. These vehicles
works in variable speed and torque conditions with single reference input: speed. The conventional
modified with the adding of second PI controller that produces optimum flux
reference. In order to test the validity and applicability of the proposed method, dynamic
been performed under different working conditions and results were presented.
The simulations results showed that the proposed method reduced remarkably the speed and the
torque ripples when compared conventional DTC method. The proposed method had
pply the conventional DTC and its extra computational load to the contro
The parameters of the blocks and the motor that used in dynamic simulations are, DC bus voltage
400V, stator phase resistance, Rs (ohm) = 0.45, stator phase inductance Ls (H) = 8.5e
hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32
C. Xia, Z. Li, and T. Shi, “A Control Strategy for Four-Switch Three-Phase Brushless DC Motor Using
Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058
constant speed
In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque
reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the
that, the BLDC motor speed and torque responses were
DTC method. The torque and speed ripples reduced remarkably with the P-
rence, the motor
, the BLDC motors have been used many industrial applications and it has gain
great popularity between electric motors. On the other hand, the DTC is well-known high
performance control method not only for induction motors but also many other motor types. This
DTC method. The proposed DTC method
. These vehicles
e input: speed. The conventional
modified with the adding of second PI controller that produces optimum flux
applicability of the proposed method, dynamic
ferent working conditions and results were presented.
The simulations results showed that the proposed method reduced remarkably the speed and the
had also very
pply the conventional DTC and its extra computational load to the controller
, DC bus voltage
phase inductance Ls (H) = 8.5e-3, flux
hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32
Phase Brushless DC Motor Using
Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058–2066, June
Computer Science & Information Technology (CS & IT) 43
[2] Z. Xiaofeng, L. Zhengyu, "A new BLDC motor drives method based on BUCK converter for torque
ripple reduction,", Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE
5th International , vol.2, no., pp.1–4, 14-16 Aug. 2006
[3] I. Topaloglu, F. Korkmaz, H. Mamur, R. Gurbuz, “Closed-Loop speed control of PM-BLDC motor fed
by six step inverter and effects of inertia changes for desktop CNC machine” Elektronika IR
Elektrotechnika, vol. 19, no 1, pp. 7–10, 2013.
[4] I. Tarimer, A. Akpunar, R. Gurbuz, “Design of a direct sliding gearless electrical motor for an
ergonomic electrical wheelchair”, Elektronika IR Elektrotechnika, no 3, pp. 75–80, 2008.
[5] I. Takahashi and T. Noguchi , “A new quick-response and high efficiency control strategy of an
induction motor” IEEE Transactions on Industrial Applications, vol.I A-22 , no.5, pp. 820–827, 1986.
[6] F. Korkmaz, I. Topaloglu, R. Gurbuz, “Simulink model of vector controlled linear induction motor with
end effect for electromagnetic launcher system”, Elektronika IR Elektrotechnika, vol. 20, no 1, pp. 29–
32, 2014.
[7] M. Nizam, A. Mujianto, H. Triwaloyo, Inayati, "Modelling on BLDC motor performance using artificial
neural network (ANN)", Rural Information & Communication Technology and Electric-Vehicle
Technology (rICT & ICeV-T), 2013 Joint International Conference on , vol., no., pp.1–4, 26-28 Nov.
2013.
[8] S. De, M. Rajne, S. Poosapati, C. Patel, K. Gopakumar, "Low-inductance axial flux BLDC motor drive
for more electric aircraft", Power Electronics, IET , vol.5, no.1, pp.124–133, January 2012.
[9] A. Tashakori, M. Hassanudeen, M. Ektesabi, "FPGA based controller drive of BLDC motor using
digital PWM technique", Power Electronics and Drive Systems (PEDS), 2015 IEEE 11th International
Conference on , vol., no., pp.658–662, 9-12 June 2015.
[10] R. Muthu, M.S. Kumaran, L.A. Rajaraman, P. Ganesh, P. Reddy, "Direct Torque Control of matrix
converter fed BLDC motor", Power Electronics (IICPE), 2014 IEEE 6th India International Conference
on , vol., no., pp.1–6, 8-10 Dec. 2014.
[11] S.B. Ozturk, W.C. Alexander, H.A. Toliyat, "Direct torque control of four-switch brushless DC Motor
with non-sinusoidal back-EMF", Power Electronics Specialists Conference, 2008. PESC 2008. IEEE ,
vol., no., pp.4730–4736, 15-19 June 2008.
[12] W.S. Im, W. Liu, J.M. Kim, "Sensorless control of 3-phase BLDC motors using DC current model",
Energy Conversion Congress and Exposition (ECCE), 2014 IEEE , vol., no., pp.4484–4490, 14-18 Sept.
2014.
[13] P.K. Girija, A. Prince, "Robustness evaluation of SMO in sensorless control of BLDC motor under DTC
scheme", Power Signals Control and Computations (EPSCICON), 2014 International Conference on ,
vol., no., pp.1-6, 6-11 Jan. 2014.
[14] F. Korkmaz, I. Topaloglu, M.F. Cakir, R. Gurbuz, "Comparative performance evaluation of FOC and
DTC controlled PMSM drives", Power Engineering, Energy and Electrical Drives (POWERENG),
2013 Fourth International Conference on , vol., no., pp.705–708, 13-17 May 2013.
[15] F. Korkmaz, M.F. Cakir, Y. Korkmaz, I. Topaloglu, “Fuzzy based stator flux optimizer design for direct
torque control”, International Journal of Instrumentation and Control Systems (IJICS), vol.2, no.4, pp.
41–49, October 2012.
44 Computer Science & Information Technology (CS & IT)
AUTHORS
Fatih Korkmaz received the B.S., M.S., and Ph.D. degrees in electrical education from
Gazi University, Ankara, Turkey, in 2000,2004 and 2011, respectively. His current major
research interests include design, control and applications of motor drive systems. From
2013, he is an assistant professor in Çankırı Karatekin University, Turkey.
Computer Science & Information Technology (CS & IT)
received the B.S., M.S., and Ph.D. degrees in electrical education from
Gazi University, Ankara, Turkey, in 2000,2004 and 2011, respectively. His current major
research interests include design, control and applications of motor drive systems. From
he is an assistant professor in Çankırı Karatekin University, Turkey.

More Related Content

PDF
BEEE machines
PDF
Electrical Drives and Controls
PDF
Electrical drive unit 1 as per IP university_EEE
PPTX
Electric drives and controls
PPT
electrical drive
PPTX
Introduction to Electrical Drive
PDF
Electric Drives and Controls Unit 1 Introduction
PDF
Ee8353 ELECTRICAL DRIVES AND CONTROL
BEEE machines
Electrical Drives and Controls
Electrical drive unit 1 as per IP university_EEE
Electric drives and controls
electrical drive
Introduction to Electrical Drive
Electric Drives and Controls Unit 1 Introduction
Ee8353 ELECTRICAL DRIVES AND CONTROL

What's hot (20)

PDF
Electrical Drive & Traction (Their Control)
DOCX
steady state analysis of dc motor
PPTX
Electric drives control
PDF
Advanced Electrical Drive Controls, Types and Implementation”
PPTX
Electric drives
PDF
Matlab simulation on chopper based speed control of dc motor: A Review
PPTX
Electric drive
PPTX
Lecture 1 to 4 introduction to electrical drive
PPTX
Factors to be considered for motor selection
PPTX
140860102043 2150207 electric drive & hybrid drive
PPTX
Electric drive systems in Robotics
PDF
Speed Torque Characteristics of BLDC Motor with Load Variations
PDF
Modelling and Simulation of DC-Motor Electric Drive Control System with Varia...
PPTX
Lecture 10, 11, 12 modes of operation
DOCX
Simulation of Automatic speed control DC Drive
PPT
DRIVERS
PDF
Electric Drive-Parts. Classification of Electric Drives, Four- Quadarant Control
PPT
Ee8353 unit i
Electrical Drive & Traction (Their Control)
steady state analysis of dc motor
Electric drives control
Advanced Electrical Drive Controls, Types and Implementation”
Electric drives
Matlab simulation on chopper based speed control of dc motor: A Review
Electric drive
Lecture 1 to 4 introduction to electrical drive
Factors to be considered for motor selection
140860102043 2150207 electric drive & hybrid drive
Electric drive systems in Robotics
Speed Torque Characteristics of BLDC Motor with Load Variations
Modelling and Simulation of DC-Motor Electric Drive Control System with Varia...
Lecture 10, 11, 12 modes of operation
Simulation of Automatic speed control DC Drive
DRIVERS
Electric Drive-Parts. Classification of Electric Drives, Four- Quadarant Control
Ee8353 unit i
Ad

Similar to A NEW APPROACH TO DTC METHOD FOR BLDC MOTOR ADJUSTABLE SPEED DRIVES (20)

PDF
MODIFIED DIRECT TORQUE CONTROL FOR BLDC MOTOR DRIVES
PDF
F044043741
PDF
A COMPARATIVE OVERVIEW TO DTC FOR PMSM DRIVEN PURE ELECTRIC VEHICLES
PDF
Review of Improved Direct Torque Control Methodologies for Induction Motor Dr...
PDF
Bt044436441
PDF
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
PDF
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
PDF
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
PDF
Closed Loop Speed Control of a BLDC Motor Drive Using Adaptive Fuzzy Tuned PI...
PDF
Review of the DTC Controller and Estimation of Stator Resistance in IM Drives
PDF
Direct torque control using neural network approach
PDF
Direct torque control using neural network approach
PDF
235420144 analysis-and-control-of-four-quadrant-operation-of-three-phase-brus...
PDF
Analysis and control of four quadrant operation of three phase brushless dc (...
PDF
Simulation Approach to Speed Control of PMBLDC Motor using Various Control Te...
PDF
[000007]
PDF
Comparitive Analysis of Speed and Position Control of BLDC Motor via Field Or...
PDF
Real time implementation of a super twisting control of a BLDC motor
PDF
International Journal of Engineering and Science Invention (IJESI)
PDF
D0262019026
MODIFIED DIRECT TORQUE CONTROL FOR BLDC MOTOR DRIVES
F044043741
A COMPARATIVE OVERVIEW TO DTC FOR PMSM DRIVEN PURE ELECTRIC VEHICLES
Review of Improved Direct Torque Control Methodologies for Induction Motor Dr...
Bt044436441
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
DTC CONTROL OF BLAC AND BLDC MOTORS FOR PURE ELECTRIC VEHICLES
Closed Loop Speed Control of a BLDC Motor Drive Using Adaptive Fuzzy Tuned PI...
Review of the DTC Controller and Estimation of Stator Resistance in IM Drives
Direct torque control using neural network approach
Direct torque control using neural network approach
235420144 analysis-and-control-of-four-quadrant-operation-of-three-phase-brus...
Analysis and control of four quadrant operation of three phase brushless dc (...
Simulation Approach to Speed Control of PMBLDC Motor using Various Control Te...
[000007]
Comparitive Analysis of Speed and Position Control of BLDC Motor via Field Or...
Real time implementation of a super twisting control of a BLDC motor
International Journal of Engineering and Science Invention (IJESI)
D0262019026
Ad

More from cscpconf (20)

PDF
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR
PDF
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATION
PDF
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...
PDF
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIES
PDF
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGIC
PDF
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS
PDF
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS
PDF
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTIC
PDF
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAIN
PDF
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...
PDF
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEM
PDF
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...
PDF
AUTOMATED PENETRATION TESTING: AN OVERVIEW
PDF
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORK
PDF
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...
PDF
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATA
PDF
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCH
PDF
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...
PDF
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGE
PDF
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXT
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATION
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIES
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGIC
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTIC
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAIN
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEM
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...
AUTOMATED PENETRATION TESTING: AN OVERVIEW
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORK
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATA
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCH
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGE
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXT

Recently uploaded (20)

PPTX
Cloud computing and distributed systems.
PDF
Diabetes mellitus diagnosis method based random forest with bat algorithm
PPTX
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
PDF
Optimiser vos workloads AI/ML sur Amazon EC2 et AWS Graviton
PDF
Mobile App Security Testing_ A Comprehensive Guide.pdf
PPTX
MYSQL Presentation for SQL database connectivity
PDF
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
PDF
Reach Out and Touch Someone: Haptics and Empathic Computing
PPTX
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
PDF
The Rise and Fall of 3GPP – Time for a Sabbatical?
PDF
Chapter 3 Spatial Domain Image Processing.pdf
DOCX
The AUB Centre for AI in Media Proposal.docx
PDF
cuic standard and advanced reporting.pdf
PPTX
Big Data Technologies - Introduction.pptx
PDF
NewMind AI Weekly Chronicles - August'25 Week I
PDF
Review of recent advances in non-invasive hemoglobin estimation
PDF
KodekX | Application Modernization Development
PDF
Architecting across the Boundaries of two Complex Domains - Healthcare & Tech...
PPTX
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
PPTX
Spectroscopy.pptx food analysis technology
Cloud computing and distributed systems.
Diabetes mellitus diagnosis method based random forest with bat algorithm
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
Optimiser vos workloads AI/ML sur Amazon EC2 et AWS Graviton
Mobile App Security Testing_ A Comprehensive Guide.pdf
MYSQL Presentation for SQL database connectivity
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
Reach Out and Touch Someone: Haptics and Empathic Computing
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
The Rise and Fall of 3GPP – Time for a Sabbatical?
Chapter 3 Spatial Domain Image Processing.pdf
The AUB Centre for AI in Media Proposal.docx
cuic standard and advanced reporting.pdf
Big Data Technologies - Introduction.pptx
NewMind AI Weekly Chronicles - August'25 Week I
Review of recent advances in non-invasive hemoglobin estimation
KodekX | Application Modernization Development
Architecting across the Boundaries of two Complex Domains - Healthcare & Tech...
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
Spectroscopy.pptx food analysis technology

A NEW APPROACH TO DTC METHOD FOR BLDC MOTOR ADJUSTABLE SPEED DRIVES

  • 1. David C. Wyld et al. (Eds) : DBDM, CICS, CSIP, AI&FL, SCOM, CSE, CCNET-2016 pp. 37–44, 2016. © CS & IT-CSCP 2016 DOI : 10.5121/csit.2016.60504 A NEW APPROACH TO DTC METHOD FOR BLDC MOTOR ADJUSTABLE SPEED DRIVES Fatih Korkmaz Department of Electric-Electronic Engineering, Çankırı Karatekin University, Uluyazı Kampüsü, Çankırı, Turkey ABSTRACT This paper proposes a new approach to direct torque control (DTC) method for brushless direct current (BLDC) motor drives. In conventional DTC method, two main reference parameters are used as: flux and torque. In this paper, the new approach has been proposed to improve the BLDC motor dynamic performance. A main difference from the conventional method of it was that only one reference parameter (speed) was used to control the BLDC motor and the second control parameter (flux) was obtained from speed error through the proposed control algorithm. Thus, the DTC performance has been especially improved on systems which need variable speed and torque during operation, like electric vehicles. The dynamic models of the BLDC and the DTC method have been created on Matlab/Simulink. The proposed method has been confirmed and verified by the dynamic simulations on different working conditions. KEY WORDS Brushless machines, Direct torque control, Vector control, Torque control 1. INTRODUCTION In recent years, the BLDC motors applications become more popular in industrial and daily utilization, like CNC machines, servo systems and electric vehicles. The main reasons of the increasing on popularity of BLDC motors, in other words, main advantages of the BLDC motors, can be listed as follows[1-4]: • High efficiencies • High power densities • High starting torque • Wide speed ranges • Linear torque and speed characteristics • Low maintenance and works in any condition The BLDC motors not only have advantages of conventional DC motors but also have advantages of AC motors as can be seen from the list. Because, they have the AC motor mechanical structures –no brushes or collectors–while they have the DC motors electrical structures. The DTC method was developed by Takahashi in the middle of the 1980s, for three phase induction motors. The DTC method converts three phase parameters of the motor (three phase voltage and currents) to two phase independent vector components with Clarke transformation, thus, it proposes
  • 2. 38 Computer Science & Information Technology (CS & IT) control of every components separately, like conventional DC motors. Although, it was developed for the induction motors, it has been applied many other motor types like permanent magnet AC motors, BLDC motors, switched reluctance motors, linear motors[5-6]. In literature, many kind of BLDC motor drive methods can be found. In [7], artificial neural networks based method was used in modeling of BLDC to get the maximum power consumption. Very simple and effective three-level neutral point clamped inverter was proposed to drive axial flux BLDC motors, in [8]. Field Programmable Gate Array (FPGA) based BLDC motor driver with using digital pulse-width modulation (PWM) is presented in [9]. In addition, several different methods, which based of the DTC, were studied in BLDC drivers. Reference [10] proposes the DTC method for matrix converter fed BLDC motor. The DTC of BLDC motor method using with four-switch inverter in constant torque region was proposed in [11]. In this paper, a new approach to the DTC method has been proposed for small sized electric vehicles that work in variable speed and torque conditions, naturally. In the proposed method, optimum stator flux reference value was obtained by PI controller with usage of the speed error. The dynamic model of the proposed method was developed with Matlab/Simulink. The dynamic simulations were performed and results were presented to illustrate the validity of the proposed method. 2. DIRECT TORQUE CONTROL OF BLDC The BLDC motor has three phase stator windings with permanent magnet rotor and electrical model of the motor that connected with PWM inverter, is given in Fig. 1[12]. Voltage equations of the motor can be obtained by the following equation; ൥ Vୟ Vୠ Vୡ ൩ = ൥ R 0 0 0 R 0 0 0 R ൩ ൥ iୟ iୠ iୡ ൩ + ൥ L 0 0 0 L 0 0 0 L ൩ ୢ ୢ୲ ൥ iୟ iୠ iୡ ൩ + ൥ eୟ eୠ eୡ ൩ (1) Where Vୟ, Vୠ, Vୡ are phase voltages, R is resistance, L is phase inductance, iୟ, iୠ, iୡ are phase currents and eୟ, eୠ, eୡ are back EMFs. Figure 1. Electrical model of the motor that connected with PWM inverter The mechanical moment equation of the motor given by the following equation; Tୣ = T୐ + Bω୫ + j ୢωౣ ୢ୲ (2) Tୣ and T୐ describes generated electromagnetic torque and load torque, respectively. B is the friction
  • 3. Computer Science & Information Technology (CS & IT) 39 coefficient, j is the inertia and ω୫ is the angular velocity of rotor[13]. The DTC method needs to transformation of the three phase motor parameters to two phase. In this transformation, electrical parameters of the motor (voltages, currents, back emf) should to be transformed to stationary reference frame and it can also be named as α − β transformation or Clarke transformation in many sources. The Clarke transformation matrix is given (3). ൤ fα fβ ൨ = ଶ ଷ ቎ 1 − ଵ ଶ − ଵ ଶ 0 √ଷ ଶ − √ଷ ଶ ቏ ൥ fୟ fୠ fୡ ൩ (3) Where, fα, fβ are α − β components of motor parameters, and fୟ, fୠ, fୡ are the abc frame components [14]. With the transforming of the three phase parameters of the motor, α − β components of the phase voltages can be written as: vୱα = Rୱiୱα + Lୱ ୢ୧౩α ୢ୲ + eα (4) vୱβ = Rୱiୱβ + Lୱ ୢ୧౩β ୢ୲ + eβ (5) Where vୱα, vୱβ are the stator voltages, iୱα, iୱβ are the stator currents and eα, eβ are back emf in the α − β referance frame. In the DTC scheme, stator flux components are obtained from α − β components of the measured stator voltages and currents as given below[15]: λୱα = ‫׬‬ሺvୱα − Rୱiୱαሻdt (6) λୱβ = ‫׬‬൫vୱβ − Rୱiୱβ൯dt (7) The magnitude of the flux can be calculated with; λ = ටλୱα ଶ + λୱβ ଶ (8) and position of the stator flux vector can be calculated with; θ = arctan λ౩β λ౩α (9) In the conventional DTC (C-DTC) method, control algorithms works with two separate reference values as torque (or speed) and flux references. Because, in idea of the DTC, stator flux vector has two components (α − β components) and they can be controlled independently from each other. One of them controls flux, while the other one controls torque. In generally, flux reference is kept constant and the speed control of the motor can be achieved by setting up the torque reference value. This approach is very appropriate for constant torque-variable speed applications. The conventional DTC block diagram is given in Fig. 2.
  • 4. 40 Computer Science & Information Technology (CS & IT) Figure 2. The conventional DTC block diagram 3. ADAPTIVE FLUX BASED METHOD A main difference from the conventional method of it was that only one reference parameter (speed) was used to control the BLDC motor and the second control parameter (flux) was obtained from speed error through the proposed control algorithm. Thus, the DTC performance has been especially improved on systems which need variable speed and torque during operation, like electric vehicles. The dynamic models of the BLDC and the DTC method have been created on Matlab/Simulink. The proposed DTC method Simulink block diagram is given in Fig. 3. In dynamic simulations, the BLDC motor was performed under two different working conditions. The parameters of the blocks and the motor that used in dynamic simulations were given in appendix. Total simulation time was 1 sec. for all conditions. The sampling time was 10 µs. The motor load constant (5Nm) and the speed reference was changed 2000 rpm to 400 rpm at 0,5. sec. in first working condition. The speed and the torque responses of the motor were given in Fig. 4 and Fig. 5, respectively. Figure 3. The proposed DTC Simulink block diagram
  • 5. Computer Science & Information Technology (CS & IT) Figure 4. Speed responses Figure 5. Torque responses Figure 6. Speed responses Computer Science & Information Technology (CS & IT) Speed responses of the BLDC in variable speed-constant load Torque responses of the BLDC in variable speed-constant load Speed responses of the BLDC in variable torque-constant speed 41 constant speed
  • 6. 42 Computer Science & Information Technology (CS & IT) Figure 7. Torque responses In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the motor were given in Fig. 6 and Fig. It can be seen in from figures (Fig. 4 improved with the P-DTC method. The torque and speed ripples reduced remarkably with the P DTC method especially in high speed reference values. In 400 rpm speed refe dynamic behaviors were almost same with both methods. 4. CONCLUSIONS Over the last decades, the BLDC motors have been used many industrial applications and it has gain great popularity between electric motors. On the other hand, the DTC is well performance control method not only for induction motors but also many other motor types. paper presents a new perspective to the applied to the BLDC motors which considered works in variable speed and torque conditions with single referenc DTC method was modified with the adding of second PI controller that produces optimum flux reference. In order to test the simulations were been performed und The simulations results showed that the proposed method reduced remarkably the speed and the torque ripples when compared conventional DTC method. The proposed method simple structure to apply the conventional DTC and its extra computational load to the contro was almost zero. APPENDIX The parameters of the blocks and the motor that used in dynamic simulations are 400V, stator phase resistance, Rs (ohm) = 0.45, stator hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32 weber, sampling time 10 µsec. REFERENCES [1] C. Xia, Z. Li, and T. Shi, “A Control Strategy for Four Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058 2009. Computer Science & Information Technology (CS & IT) Torque responses of the BLDC in variable torque-constant speed In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the and Fig. 7, respectively. from figures (Fig. 4–Fig. 7) that, the BLDC motor speed and torque responses were DTC method. The torque and speed ripples reduced remarkably with the P DTC method especially in high speed reference values. In 400 rpm speed reference, the motor dynamic behaviors were almost same with both methods. , the BLDC motors have been used many industrial applications and it has gain great popularity between electric motors. On the other hand, the DTC is well performance control method not only for induction motors but also many other motor types. paper presents a new perspective to the conventional DTC method. The proposed DTC method the BLDC motors which considered drives small size electric vehicles. These vehicles works in variable speed and torque conditions with single reference input: speed. The conventional modified with the adding of second PI controller that produces optimum flux reference. In order to test the validity and applicability of the proposed method, dynamic been performed under different working conditions and results were presented. The simulations results showed that the proposed method reduced remarkably the speed and the torque ripples when compared conventional DTC method. The proposed method had pply the conventional DTC and its extra computational load to the contro The parameters of the blocks and the motor that used in dynamic simulations are, DC bus voltage 400V, stator phase resistance, Rs (ohm) = 0.45, stator phase inductance Ls (H) = 8.5e hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32 C. Xia, Z. Li, and T. Shi, “A Control Strategy for Four-Switch Three-Phase Brushless DC Motor Using Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058 constant speed In the second test, the motor was simulated at constant speed reference (2000 rpm) and the torque reference was changed to 1 Nm to 5 Nm at 0,5. sec. The speed and the torque responses of the that, the BLDC motor speed and torque responses were DTC method. The torque and speed ripples reduced remarkably with the P- rence, the motor , the BLDC motors have been used many industrial applications and it has gain great popularity between electric motors. On the other hand, the DTC is well-known high performance control method not only for induction motors but also many other motor types. This DTC method. The proposed DTC method . These vehicles e input: speed. The conventional modified with the adding of second PI controller that produces optimum flux applicability of the proposed method, dynamic ferent working conditions and results were presented. The simulations results showed that the proposed method reduced remarkably the speed and the had also very pply the conventional DTC and its extra computational load to the controller , DC bus voltage phase inductance Ls (H) = 8.5e-3, flux hysteresis band limits = ±0.005, torque hysteresis band limits = ±0.02, stator flux reference = 0.32 Phase Brushless DC Motor Using Single Current Sensor”, Industrial Electronics, IEEE Transactions on , vol.56, no.6, pp. 2058–2066, June
  • 7. Computer Science & Information Technology (CS & IT) 43 [2] Z. Xiaofeng, L. Zhengyu, "A new BLDC motor drives method based on BUCK converter for torque ripple reduction,", Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International , vol.2, no., pp.1–4, 14-16 Aug. 2006 [3] I. Topaloglu, F. Korkmaz, H. Mamur, R. Gurbuz, “Closed-Loop speed control of PM-BLDC motor fed by six step inverter and effects of inertia changes for desktop CNC machine” Elektronika IR Elektrotechnika, vol. 19, no 1, pp. 7–10, 2013. [4] I. Tarimer, A. Akpunar, R. Gurbuz, “Design of a direct sliding gearless electrical motor for an ergonomic electrical wheelchair”, Elektronika IR Elektrotechnika, no 3, pp. 75–80, 2008. [5] I. Takahashi and T. Noguchi , “A new quick-response and high efficiency control strategy of an induction motor” IEEE Transactions on Industrial Applications, vol.I A-22 , no.5, pp. 820–827, 1986. [6] F. Korkmaz, I. Topaloglu, R. Gurbuz, “Simulink model of vector controlled linear induction motor with end effect for electromagnetic launcher system”, Elektronika IR Elektrotechnika, vol. 20, no 1, pp. 29– 32, 2014. [7] M. Nizam, A. Mujianto, H. Triwaloyo, Inayati, "Modelling on BLDC motor performance using artificial neural network (ANN)", Rural Information & Communication Technology and Electric-Vehicle Technology (rICT & ICeV-T), 2013 Joint International Conference on , vol., no., pp.1–4, 26-28 Nov. 2013. [8] S. De, M. Rajne, S. Poosapati, C. Patel, K. Gopakumar, "Low-inductance axial flux BLDC motor drive for more electric aircraft", Power Electronics, IET , vol.5, no.1, pp.124–133, January 2012. [9] A. Tashakori, M. Hassanudeen, M. Ektesabi, "FPGA based controller drive of BLDC motor using digital PWM technique", Power Electronics and Drive Systems (PEDS), 2015 IEEE 11th International Conference on , vol., no., pp.658–662, 9-12 June 2015. [10] R. Muthu, M.S. Kumaran, L.A. Rajaraman, P. Ganesh, P. Reddy, "Direct Torque Control of matrix converter fed BLDC motor", Power Electronics (IICPE), 2014 IEEE 6th India International Conference on , vol., no., pp.1–6, 8-10 Dec. 2014. [11] S.B. Ozturk, W.C. Alexander, H.A. Toliyat, "Direct torque control of four-switch brushless DC Motor with non-sinusoidal back-EMF", Power Electronics Specialists Conference, 2008. PESC 2008. IEEE , vol., no., pp.4730–4736, 15-19 June 2008. [12] W.S. Im, W. Liu, J.M. Kim, "Sensorless control of 3-phase BLDC motors using DC current model", Energy Conversion Congress and Exposition (ECCE), 2014 IEEE , vol., no., pp.4484–4490, 14-18 Sept. 2014. [13] P.K. Girija, A. Prince, "Robustness evaluation of SMO in sensorless control of BLDC motor under DTC scheme", Power Signals Control and Computations (EPSCICON), 2014 International Conference on , vol., no., pp.1-6, 6-11 Jan. 2014. [14] F. Korkmaz, I. Topaloglu, M.F. Cakir, R. Gurbuz, "Comparative performance evaluation of FOC and DTC controlled PMSM drives", Power Engineering, Energy and Electrical Drives (POWERENG), 2013 Fourth International Conference on , vol., no., pp.705–708, 13-17 May 2013. [15] F. Korkmaz, M.F. Cakir, Y. Korkmaz, I. Topaloglu, “Fuzzy based stator flux optimizer design for direct torque control”, International Journal of Instrumentation and Control Systems (IJICS), vol.2, no.4, pp. 41–49, October 2012.
  • 8. 44 Computer Science & Information Technology (CS & IT) AUTHORS Fatih Korkmaz received the B.S., M.S., and Ph.D. degrees in electrical education from Gazi University, Ankara, Turkey, in 2000,2004 and 2011, respectively. His current major research interests include design, control and applications of motor drive systems. From 2013, he is an assistant professor in Çankırı Karatekin University, Turkey. Computer Science & Information Technology (CS & IT) received the B.S., M.S., and Ph.D. degrees in electrical education from Gazi University, Ankara, Turkey, in 2000,2004 and 2011, respectively. His current major research interests include design, control and applications of motor drive systems. From he is an assistant professor in Çankırı Karatekin University, Turkey.