Torque Ripple Minimization of BLDC Motor using Fuzzy Logic

2. content
 Abstract
 Introduction
 Literature Review
 Block diagram
 Block diagram description
 Methodology
 Hardware requirement
 Software requirement
 Conclusion
 Advantage
 Application
 References

3. Abstract
 This project presents a Fuzzy Logic Controller (FLC) for speed
control of a BLDC by using. The Fuzzy Logic (FL) approach
applied to speed control leads to an improved dynamic behavior
of the motor drive system and an immune to load perturbations
and parameter variations. The FLC is designed using based on a
simple analogy between the control surfaces of the FLC and a
given Proportional-Integral controller (PIC) for the same
application. Fuzzy logic control offers an improvement in the
quality of the speed response, compared to PI control. This work
focuses on investigation and evaluation of the performance of a
permanent magnet brushless DC motor (PMBLDC) drive,
controlled by PI, and Fuzzy logic speed controllers. The
Controllers are for the PMBLDC motor drive simulated using
MATLAB software package. Further, the PI controller has been
implemented on an experimental BLDC motor set up.

4. Introduction
 In variable speed operations of BLDC motor, the PI control
is still the most used control. This is because of its
simplicity and ease of design.
 However, it has disadvantages that the performance
depends to proportional and integral gains. Therefore,
when the operating condition changes such as
disturbances, load changes and motor's parameters
variations, the retuning process of control gains in
necessary.
 Controllers using artificial intelligent tools, such as fuzzy
logic and neural network can be applied to overcome
foregoing problems.

5. Introduction
 Different intelligent controllers such as Fuzzy logic
controllers (FLC) and Neural Network controllers have
been explored. They may control the speed directly or
as indirectly adjust the gains of PI controller.
 This project presents an implementation of Fuzzy
Logic controller for improving the transient responses
to torque disturbance and speed reference following of
the BLDC motor drive.
 Simulation results are used to show the abilities and
shortcomings of the proposed method as compared
with the conventional PI and fuzzy controllers.

6. PROBLEM STATEMENT
 The Fuzzy Logic (FL) approach applied to speed
control leads to an improved dynamic behavior of the
motor drive system and an immune to load
perturbations and parameter variations. Fuzzy logic
control offers an improvement in the quality of the
speed response.
 Most of these controllers use mathematical models
and are sensitive to parametric variations. These
controllers are inherently robust to load disturbances.
Besides, fuzzy logic controllers can be easily
implemented.

7. LITERATURE REVIEW
 The BLDCM drive system’s commutation torque pulsation is
mostly responsible for aberrant vibration, undesired speed
fluctuations, and sound.
 To maximize BLDCM drive system torque performance, it is
necessary to minimize the commutation torque pulsation.
 A composite switching mode has been proposed to reduce the
torque ripple at all speeds during commutation periods during
the inverter’s 120° and 180° electrical conduction modes.
 A variable input voltage solution for efficient torque ripple
reduction during the BLDCM’s freewheeling period was reported
in.
 With this approach, the Laplace transformation was used to
predict the freewheeling zone and the ideal voltage.

8. Block diagram

9. BLOCK DIAGRAM DESCRIPTION
 The IPM type used in these studies is PEC16DSM01, its
rated voltage is 1200V, rated current is 25A, the control
voltage is 20V and the switching frequency is 20 KHz. The
experimental setup block diagram of BLDC motor diagram
consists of following systems.
1. Intelligent power module
2. Voltage and current sensor
3. Signal conditioner
4. Protection circuit
5. Opt coupler
6. 3φ diode bridge rectifier
7. Speed sensor
8. Frequency to voltage converter

10. METHODOLOGY
 Fuzzy representation is the technique of telling the
distinctiveness of a scheme utilizing fuzzy presumption rules.
 The technique has a characteristic quality in that it can convey
linguistically composite non-linear scheme. It is though,
extremely hand to recognize the policy and tune the
membership functions of the analysis.
 Fuzzy organizers are usually built with fuzzy policies. These
fuzzy policies are getting either from domain experts or by
scrutinizing the people who are at present doing the control.
 The membership capacities for the fuzzy sets will get from the
data reachable from the space specialists as well as watched
control activities.

11. METHODOLOGY
 The working of such approaches and participation
capacities require tuning. That is, execution of the
controller must be estimated and the enrollment
capacities and standards balanced in view of the
execution. This procedure will be tedious. The
fundamental arrangement of Fuzzy rationale control
based consists of four main parts i.e.
(i) Fuzzification,
(ii) knowledge base,
(iii) Inference Engine and
(iv) Defuzzification.

12. HARDWARE REQUIREMENT
• System: Pentium IV 2.4 GHz.
• Hard Disk: 40 GB.
• Floppy Drive: 1.44 Mb.
• Monitor: 15 VGA Colour.
• Mouse: Logitech.
• RAM: 512 Mb.

13. SOFTWARE REQUIREMENT
• Operating system: Windows XP/7.
• Coding Language: MATLAB
• Tool: MATLAB R 2012

14. ADVANTAGE
 High dynamic response
 High efficiency
 Long operating life
 Noiseless operation
 Higher speed ranges

15. APPLICATIONS:
 BLDC motors find applications in every segment of the
market. Such as, appliances, industrial control,
automation, aviation and so on. We can categorize the
BLDC motor control into three major types such as
 Constant load
 Varying loads
 Positioning applications

16. CONCLUSION
 A fuzzy logic controller (FLC) has been employed for the
speed control of PMBLDC motor drive and analysis of
results of the performance of a fuzzy controller is
presented. The modelling and simulation of the complete
drive system is described in this thesis. Effectiveness of the
model is established by performance prediction over a wide
range of operating conditions.
 A performance comparison between the fuzzy logic
controller and the conventional PI controller has been
carried out by simulation runs confirming the validity and
superiority of the fuzzy logic controller for implementing
the fuzzy logic controller to be adjusted such that manual
tuning time of the classical controller is significantly
reduced.

17. REFERENCES
 T. M. Jahns and W. L. Soong, "Pulsating torque minimization
techniques for permanent magnet AC motor drives-a review", IEEE
Trans. on Industrial Electronics, vol. 43, 321-330, 1996.
 Z. Cunshan and B. Dunxin, "A PWM control algorithm for eliminating
torque ripple caused by stator magnetic field jump of brushless DC
motors", in Intelligent Control and Automation,2008. WCICA 2008.
The 7th World Congress on, 2008, 6547-6549.
 K. Wei, Kun, H. Chang-sheng, Z. Zhong-chao, "A novel PWM scheme
to eliminate the diode freewheeling in the inactive phase in BLDC
motor", Frontiers of Electrical and Electronic Engineering in China,
vol. 1, 194-198, 2006.
 X. Zhang and B. Chen, "The different influences of four PWM modes
on the commutation torque ripples in sensorless brushless DC motors
control system," in Electrical Machines and Systems, ICEMS 2001.
Proceedings of the Fifth International Conference on, 2001, 575-578
vol.1.

18. Thank You….